Systems and methods for correcting mismatch induced by respiratory motion in positron emission tomography image reconstruction

ABSTRACT

The disclosure relates to PET imaging systems and methods. The systems may execute the methods to obtain an anatomical image and PET data of a subject, and gate the PET data into a plurality of bins. The systems may execute the methods to reconstruct a plurality of gated PET images based on the gated PET data. The systems may execute the methods to determine a motion vector field corresponding to a target respiratory phase with respect to a reference respiratory phase relating to the anatomical image. The systems may execute the methods to obtain a respiratory phase-matched anatomical image for the target respiratory phase by transforming a VOI in the anatomical image based on the motion vector field corresponding to the target respiratory phase with respect to the reference respiratory phase, and reconstructing an attenuation corrected PET image corresponding to the target respiratory phase.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/881,765, filed on Jan. 27, 2018, the contents of which are herebyincorporated by reference.

TECHNICAL FIELD

The present disclosure generally relates to systems and methods forimage processing, and more specifically relates to methods and systemsfor correcting mismatch induced by respiratory motion in positronemission tomography (PET) image reconstruction.

BACKGROUND

PET is a specialized radiology procedure that generatesthree-dimensional images of functional processes in a target organ ortissue of a subject. Specifically, in PET studies, biologically activemolecules carrying radioactive tracer molecules are first introducedinto the subject. The PET system then detects pairs of gamma raysemitted indirectly by the tracer and reconstructs an image of the tracerconcentration within the subject by analyzing the detected signals.Because the biologically active molecules used in PET studies arenatural substrates of metabolism at the target organ or tissue, PET canevaluate the physiology (functionality) of the target organ or tissue,as well as its biochemical properties. Changes in these properties ofthe target organ or tissue may provide information for theidentification of the onset or progression of a disease before ananatomical change relating to the disease become detectable by otherdiagnostic tests, such as computed tomography (CT) or magnetic resonanceimaging (MRI).

Furthermore, the high sensitivity of PET—in the picomolar range—mayallow the detection of small amounts of radio-labeled markers in vivo.PET may be used in conjunction with other diagnostic tests to achievesimultaneous acquisition of both structural and functional informationof the subject. Examples include a PET/CT hybrid system, a PET/MR hybridsystem.

PET and CT data of a subject may be obtained using a PET/CT hybridsystem. The CT data may be applied in the attenuation correction of thePET data. During a scan in the PET/CT system, a subject may undergorespiratory motion. When the scanning is performed for chest or upperabdomen examinations, respiratory motion of the lungs and/or cardiacmotion of the heart of the subject may lead to a mismatch between thePET data and the CT data. The mismatch may subsequently cause artifactsin the PET image, which in turn may affect an interpretation of the PETimage, or a diagnosis performed on the basis of the PET image. A CT scanis quick and the CT data may correspond to the same or substantially thesame respiratory phase. A PET scan is relatively slow and the PET datamay correspond to a plurality of respiratory phases, which may lead to amismatch between the CT data and the PET data. Thus, it is desirable todevelop a method and system for matching the CT data and the PET data toreduce the effect of respiratory and/or cardiac motion of the subjectand improve the quality of a PET image reconstructed accordingly.

SUMMARY

In a first aspect of the present disclosure, a method for imageprocessing may be implemented on at least one machine, each of which mayhave a processor and a storage device. The method may include one ormore of the following operations. An anatomical image and PET data of asubject may be obtained. The PET data may be gated into a plurality ofbins. The plurality of bins may correspond to a plurality of respiratoryphases. A plurality of gated PET images may be reconstructed based onthe gated PET data. Each gated PET image of the plurality of gated PETimages may correspond to a respiratory phase of the plurality ofrespiratory phases. A motion vector field corresponding to a targetrespiratory phase with respect to a reference respiratory phase may bedetermined based on the plurality of gated PET images and the anatomicalimage. The reference respiratory phase may be related to the anatomicalimage. A respiratory phase-matched anatomical image for the targetrespiratory phase may be obtained by transforming a volume of interest(VOI) in the anatomical image based on the motion vector fieldcorresponding to the target respiratory phase with respect to thereference respiratory phase. An attenuation corrected PET imagecorresponding to the target respiratory phase may be reconstructed basedon the respiratory phase-matched anatomical image and the gated PETdata.

In some embodiments, the PET data may include a first portion and asecond portion. The first portion may be affected more by a respiratorymotion of the subject than the second portion. The first portion maycorrespond to the VOI in the anatomical image.

In some embodiments, the determining a motion vector field correspondingto a target respiratory phase with respect to a reference respiratoryphase may include one or more of the following operations. The referencerespiratory phase that matches a respiratory phase of the anatomicalimage may be identified among the plurality of respiratory phases basedon the plurality of gated PET images. The motion vector fieldcorresponding to the target respiratory phase may be determined based ona gated PET image corresponding to the target respiratory phase and areference gated PET image corresponding to the reference respiratoryphase.

In some embodiments, the identifying the reference respiratory phasethat matches the respiratory phase of the anatomical image may includeone or more of the following operations. One or more sub-regions in theanatomical image may be identified. The one or more sub-regions maycorrespond to at least a portion of a lung and a portion of a liver ofthe subject. The reference respiratory phase that matches therespiratory phase of the anatomical image may be determined among theplurality of the respiratory phases based on the identified one or moresub-regions in the anatomical image and one or more correspondingportions in each gated PET image of the plurality of gated PET images.

In some embodiments, the one or more sub-regions include a firstsub-region and a second sub-region. The identifying one or moresub-regions in the anatomical image may include one or more of thefollowing operations. A left lung and a right lung of the subject in theanatomical image may be segmented. The first sub-region may bedetermined based on the left lung. The second sub-region may bedetermined based on the right lung.

In some embodiments, the determining the reference respiratory phasethat matches the respiratory phase of the anatomical image may includeone or more of the following operations. For each of the identified oneor more sub-regions of the anatomical image, a candidate referencerespiratory phase may be determined based on the sub-region of theanatomical image and corresponding portions in the plurality of gatedPET images. One candidate reference respiratory phase may be designatedfrom the candidate reference respiratory phases as the referencerespiratory phase that matches the respiratory phase of the anatomicalimage.

In some embodiments, for a sub-region in the anatomical image, thedetermining a candidate reference respiratory phase of the anatomicalimage may include one or more of the following operations. For each ofthe plurality of gated PET images, a similarity between the sub-regionin the anatomical image and the corresponding portion in the gated PETimage may be determined. A highest similarity among the determinedsimilarities may be identified. The respiratory phase of the gated PETimage with the highest similarity may be designated as the candidatereference respiratory phase of the anatomical image.

In some embodiments, the determining a similarity between the sub-regionin the anatomical image and the corresponding portion in the gated PETimage may be based on at least one of pixel-based similarity,entropy-based similarity, mutual information similarity, orcontour-based similarity.

In some embodiments, the motion vector field corresponding to a targetrespiratory phase may be determined by registering the gated PET imagecorresponding to the target respiratory phase with the reference gatedPET image corresponding to the reference respiratory phase.

In some embodiments, the gated PET image with the reference gated PETimage may be registered based on at least one of an optical flowregistration algorithm, a demons registration algorithm, or a B-splineregistration algorithm.

In some embodiments, the segmenting the VOI in the anatomical image mayinclude one or more of the following operations. In the anatomicalimage, one or more bones surrounding the thoracic and abdominal cavityof the subject located within the scanning region may be segmented. Oneor more edge points of the one or more bones may be determined. The VOImay be determined based on the one or more edge points.

In some embodiments, the method may further include one or more of thefollowing operations. For each respiratory phase, a motion vector fieldcorresponding to the respiratory phase may be determined by an imageregistration. For each respiratory phase, a respiratory phase-matchedanatomical image may be obtained by transforming the VOI in theanatomical image to generate a corrected anatomical image correspondingto the respiratory phase based on the corresponding motion vector field.For each respiratory phase, an attenuation corrected PET imagecorresponding to the respiratory phase may be reconstructed based on thecorresponding corrected anatomical image and the gated PET data.

In some embodiments, the anatomical image may be at least one of acomputed tomography (CT) image or a magnetic resonance (MR) image.

In some embodiments, the PET data may be acquired by a PET scanner witha PET field of view (FOV). The obtaining of the PET data may includeacquiring the PET data by locating the at least a portion of the lungand a portion of the liver of the subject in a central region of the PETFOV of the PET scanner.

In a second aspect of the present disclosure, a system may include atleast one processor and at least one storage medium for storinginstructions. When executing the instructions, the at least oneprocessor may be directed to perform a method including one or more ofthe following operations. An anatomical image and PET data of a subjectmay be obtained. The PET data may be gated into a plurality of bins. Theplurality of bins may correspond to a plurality of respiratory phases. Aplurality of gated PET images may be reconstructed based on the gatedPET data. Each gated PET image of the plurality of gated PET images maycorrespond to a respiratory phase of the plurality of respiratoryphases. A motion vector field corresponding to a target respiratoryphase with respect to a reference respiratory phase may be determinedbased on the plurality of gated PET images and the anatomical image. Thereference respiratory phase may be related to the anatomical image. Arespiratory phase-matched anatomical image for the target respiratoryphase may be obtained by transforming a VOI in the anatomical imagebased on the motion vector field corresponding to the target respiratoryphase with respect to the reference respiratory phase. An attenuationcorrected PET image corresponding to the target respiratory phase may bereconstructed based on the respiratory phase-matched anatomical imageand the gated PET data.

In a third aspect of the present disclosure, a non-transitorycomputer-readable storage medium may store instructions that, whenexecuted by at least one processor of a system, cause the system toperform a method including one or more of the following operations. Ananatomical image and PET data of a subject may be obtained. The PET datamay be gated into a plurality of bins. The plurality of bins maycorrespond to a plurality of respiratory phases. A plurality of gatedPET images may be reconstructed based on the gated PET data. Each gatedPET image of the plurality of gated PET images may correspond to arespiratory phase of the plurality of respiratory phases. A motionvector field corresponding to a target respiratory phase with respect toa reference respiratory phase may be determined based on the pluralityof gated PET images and the anatomical image. The reference respiratoryphase may be related to the anatomical image. A respiratoryphase-matched anatomical image for the target respiratory phase may beobtained by transforming a VOI in the anatomical image based on themotion vector field corresponding to the target respiratory phase withrespect to the reference respiratory phase. An attenuation corrected PETimage corresponding to the target respiratory phase may be reconstructedbased on the respiratory phase-matched anatomical image and the gatedPET data.

In a fourth aspect of the present disclosure, a system may include atleast one processor and storage. The system may include an acquisitionmodule and a processing module. The acquisition module may be directedto obtain an anatomical image and PET data of a subject. The processingmodule may include a gating unit, a reconstruction unit, a motion vectorfield determination unit, and a transformation unit. The gating unit maybe directed to gate the PET data into a plurality of bins, the pluralityof bins corresponding to a plurality of respiratory phases. Thereconstruction unit may be directed to reconstruct, based on the gatedPET data, a plurality of gated PET images. Each gated PET image of theplurality of gated PET images may correspond to a respiratory phase ofthe plurality of respiratory phases. The motion vector fielddetermination unit may be directed to determine, based on the pluralityof gated PET images and the anatomical image, a motion vector fieldcorresponding to a target respiratory phase with respect to a referencerespiratory phase relating to the anatomical image. The transformationunit may be directed to obtain a respiratory phase-matched anatomicalimage for the target respiratory phase by transforming a VOI in theanatomical image based on the motion vector field corresponding to thetarget respiratory phase with respect to the reference respiratoryphase. The reconstruction unit may be further directed to reconstruct,based on the respiratory phase-matched anatomical image and the gatedPET data, an attenuation corrected PET image corresponding to the targetrespiratory phase.

Additional features will be set forth in part in the description whichfollows, and in part will become apparent to those skilled in the artupon examination of the following and the accompanying drawings or maybe learned by production or operation of the examples. The features ofthe present disclosure may be realized and attained by practice or useof various aspects of the methodologies, instrumentalities, andcombinations set forth in the detailed examples discussed below.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is further described in terms of exemplaryembodiments. These exemplary embodiments are described in detail withreference to the drawings. These embodiments are non-limiting exemplaryembodiments, in which like reference numerals represent similarstructures throughout the several views of the drawings, and wherein:

FIG. 1 is a schematic diagram illustrating an exemplary imaging systemaccording to some embodiments of the present disclosure;

FIG. 2 is a schematic diagram illustrating exemplary hardware andsoftware components of a computing device on which data processingsystem or a portion thereof may be implemented according to someembodiments of the present disclosure;

FIG. 3 is a schematic diagram illustrating exemplary hardware and/orsoftware components of a mobile device on which a use terminal may beimplemented according to some embodiments of the present disclosure;

FIG. 4 is a block diagram illustrating an exemplary data processingsystem according to some embodiments of the present disclosure;

FIG. 5 is a block diagram illustrating an exemplary processing moduleaccording to some embodiments of the present disclosure;

FIG. 6 is a flowchart illustrating an exemplary process forreconstructing an attenuation corrected PET image according to someembodiments of the present disclosure;

FIG. 7 is a flowchart illustrating an exemplary process for gating PETdata according to some embodiments of the present disclosure;

FIG. 8A is a flowchart illustrating an exemplary process for determininga reference respiratory phase of a CT image according to someembodiments of the present disclosure;

FIG. 8B is a flowchart illustrating an exemplary process for determininga candidate reference respiratory phase of a CT image according to someembodiments of the present disclosure;

FIG. 9 is a flowchart illustrating an exemplary process for determininga volume of interest (VOI) in a CT image according to some embodimentsof the present disclosure;

FIGS. 10A to 10C illustrate exemplary sub-regions in a CT imageaccording to some embodiments of the present disclosure;

FIGS. 11A and 11B illustrate exemplary edge points of bones within athoracic and abdominal cavity of a subject according to some embodimentsof the present disclosure;

FIG. 11C illustrates an exemplary rear surface of a thoracic andabdominal cavity according to some embodiments of the presentdisclosure;

FIG. 11D illustrates exemplary a front surface and a rear surface of athoracic and abdominal cavity according to some embodiments of thepresent disclosure;

FIG. 11E illustrates a transversal plane of a boundary of an exemplaryVOI in a CT image according to some embodiments of the presentdisclosure; and

FIGS. 12A to 12C illustrate an exemplary VOI in a CT image according tosome embodiments of the present disclosure.

DETAILED DESCRIPTION

In the following detailed description, numerous specific details are setforth by way of examples in order to provide a thorough understanding ofthe relevant disclosure. However, it should be apparent to those skilledin the art that the present disclosure may be practiced without suchdetails. In other instances, well-known methods, procedures, systems,components, and/or circuitry have been described at a relativelyhigh-level, without detail, in order to avoid unnecessarily obscuringaspects of the present disclosure. Various modifications to thedisclosed embodiments will be readily apparent to those skilled in theart, and the general principles defined herein may be applied to otherembodiments and applications without departing from the spirit and scopeof the present disclosure. Thus, the present disclosure is not limitedto the embodiments shown, but to be accorded the widest scope consistentwith the claims.

The terminology used herein is for the purpose of describing particularexample embodiments only and is not intended to be limiting. As usedherein, the singular forms “a,” “an,” and “the” may be intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprise,”“comprises,” and/or “comprising,” “include,” “includes,” and/or“including,” when used in this specification, specify the presence ofstated features, integers, steps, operations, elements, and/orcomponents, but do not preclude the presence or addition of one or moreother features, integers, steps, operations, elements, components,and/or groups thereof.

It will be understood that the term “system,” “engine,” “unit,”“module,” and/or “block” used herein are one method to distinguishdifferent components, elements, parts, section or assembly of differentlevel in ascending order. However, the terms may be displaced by anotherexpression if they achieve the same purpose.

Generally, the word “module,” “unit,” or “block,” as used herein, refersto logic embodied in hardware or firmware, or to a collection ofsoftware instructions. A module, a unit, or a block described herein maybe implemented as software and/or hardware and may be stored in any typeof non-transitory computer-readable medium or other storage device. Insome embodiments, a software module/unit/block may be compiled andlinked into an executable program. It will be appreciated that softwaremodules can be callable from other modules/units/blocks or fromthemselves, and/or may be invoked in response to detected events orinterrupts. Software modules/units/blocks configured for execution oncomputing devices may be provided on a computer-readable medium, such asa compact disc, a digital video disc, a flash drive, a magnetic disc, orany other tangible medium, or as a digital download (and can beoriginally stored in a compressed or installable format that needsinstallation, decompression, or decryption prior to execution). Suchsoftware code may be stored, partially or fully, on a storage device ofthe executing computing device, for execution by the computing device.Software instructions may be embedded in a firmware, such as an erasableprogrammable read-only memory (EPROM). It will be further appreciatedthat hardware modules/units/blocks may be included in connected logiccomponents, such as gates and flip-flops, and/or can be included ofprogrammable units, such as programmable gate arrays or processors. Themodules/units/blocks or computing device functionality described hereinmay be implemented as software modules/units/blocks, but may berepresented in hardware or firmware. In general, themodules/units/blocks described herein refer to logicalmodules/units/blocks that may be combined with othermodules/units/blocks or divided into sub-modules/sub-units/sub-blocksdespite their physical organization or storage. The description may beapplicable to a system, an engine, or a portion thereof.

It will be understood that when a unit, engine, module or block isreferred to as being “on,” “connected to,” or “coupled to,” anotherunit, engine, module, or block, it may be directly on, connected orcoupled to, or communicate with the other unit, engine, module, orblock, or an intervening unit, engine, module, or block may be present,unless the context clearly indicates otherwise. As used herein, the term“and/or” includes any and all combinations of one or more of theassociated listed items.

These and other features, and characteristics of the present disclosure,as well as the methods of operation and functions of the relatedelements of structure and the combination of parts and economies ofmanufacture, may become more apparent upon consideration of thefollowing description with reference to the accompanying drawings, allof which form a part of this disclosure. It is to be expresslyunderstood, however, that the drawings are for the purpose ofillustration and description only and are not intended to limit thescope of the present disclosure. It is understood that the drawings arenot to scale.

Provided herein are systems and components for non-invasive imaging,such as for disease diagnosis or research purposes. In some embodiments,the imaging system may be a computed tomography (CT) system, a magneticresonance imaging (MRI) system, a positron emission tomography (PET)system, a PET-CT system, a PET-MRI system, or the like, or anycombination thereof.

The following description is provided to help better understandingPET/CT image reconstruction methods and/or systems. The term “image”used in this disclosure may refer to a 2D image, a 3D image, a 4D image,and/or any related image data (e.g., CT data, projection datacorresponding to the CT data). The term “segment an organ” (e.g., alung, the liver of a subject) used in this disclosure may refer tosegment a portion of an image corresponding to the organ. This is notintended to limit the scope the present disclosure. For persons havingordinary skills in the art, a certain amount of variations, changes,and/or modifications may be deducted under the guidance of the presentdisclosure. Those variations, changes, and/or modifications do notdepart from the scope of the present disclosure.

The present disclosure relates to systems and methods for reconstructingan attenuation corrected PET image. The systems and methods mayreconstruct the attenuation corrected PET image based on PET data and ananatomical image. The anatomical image may include a CT image or an MRimage. For illustration purposes, the reconstruction of an attenuationcorrected PET image based on the CT image is described as an example inthe present disclosure. The PET data and the CT image may correspond toa same scanning region of the subject. The PET data may be gated toreconstruct a plurality of gated PET images corresponding to a pluralityof respiratory phases. One or more sub-regions corresponding to at leasta portion of a lung and at least a portion of a liver of the subject maybe identified in the CT image. Based on the sub-regions, a referencerespiratory phase of the CT image may be determined among the pluralityof the respiratory phases. A gated PET image corresponding to a targetrespiratory phase may be registered with a reference gated PET imagecorresponding to the reference respiratory phase to determine a motionvector field corresponding to the target respiratory phase with respectto the reference respiratory phase. The CT image may be transformedbased on the motion vector field to generate a respiratory phase-matchedCT image corresponding to the target respiratory phase. An attenuationcorrected PET image corresponding to the target respiratory phase may bereconstructed based on the gated PET data and the respiratoryphase-matched CT image corresponding to the target respiratory phase.

FIG. 1 illustrates an exemplary imaging system 100 according to someembodiments of the present disclosure. An imaging system 100 may acquirean image of a subject. As illustrated, the imaging system 100 mayinclude an imaging device 110, a controller 120, a data processingsystem 130, an input/output device 140, a network 160, and a terminal(s)170, a gating system 180, and storage 190.

In some embodiments, the imaging device 110 may scan a subject, andacquire data relating to the subject. In some embodiments, the imagingdevice 110 may be, for example, a PET device, a CT device, an MRIdevice, or the like, or any combination thereof (e.g., a PET-CT device,a PET-MRI device, or a CT-MRI device). In some embodiments, the imagingdevice 110 may be a radiation imaging device. The radiation imagingdevice may include a radiation source to emit radioactive rays to thesubject to be scanned. The radioactive rays may include, for example,particle rays, photon rays, or the like, or any combination thereof. Theparticle rays may include neutrons, protons, electrons, μ-mesons, heavyions, or the like, or any combination thereof. The photon rays mayinclude X-ray, γ-ray, α-ray, β-ray, ultraviolet, laser, or the like, orany combination thereof.

In some embodiments, the imaging device 110 may be a PET/CT imagingdevice including a gantry 111, a detector 112, a field of view (FOV)113, a table 114, and a radiation source 115. The gantry 111 may supportthe detector 112 and the radiation source 115. A subject may be placedon the table 114 and moved into the FOV 113 for scanning along the zaxis as illustrated in FIG. 1. The radiation source 115 may emitradioactive rays to the subject. The detector 112 may detect radiationevents (e.g., gamma photons) emitted from the FOV 113. In someembodiments, the detector 112 may include one or more detector units.The detector 112 may include a scintillation detector (e.g., a cesiumiodide detector), a gas detector, etc. The detector 112 may be and/orinclude a single-row detector in which a plurality of detector units arearranged in a single row and/or a multi-row detector in which aplurality of detector units are arranged in multiple rows.

The controller 120 may control the imaging device 110, the input/outputdevice 140, and/or the data processing system 130. In some embodiments,the controller 120 may control the X-ray generation unit and/or theX-ray detection unit (if any) of the imaging device 110. The controller120 may receive information from or send information to the imagingdevice 110, the input/output device 140, and/or the data processingsystem 130. For example, the controller 120 may receive commands fromthe input/output device 140 provided by a user. As a further example,the controller 120 may control the imaging device 110, the input/outputdevice 140, and/or the data processing system 130 according to thereceived commands or transformed commands. As still a further example,the controller 120 may send image signals or data to the data processingsystem 130. In some embodiments, the controller 120 may include acomputer, a program, an algorithm, software, a storage device, one ormore interfaces, etc. Exemplary interfaces may include the interfaceswith the imaging device 110, the input/output device 140, the dataprocessing system 130, and/or other modules or units in the imagingsystem 100.

In some embodiments, the controller 120 may receive a command providedby a user including, for example, an imaging technician, a doctor, etc.Exemplary commands may relate to a scan time, a location of the subject,the location of a table on which the subject lies, a rotation speed ofthe gantry, a specific parameter relating to a threshold that may beused in the image reconstruction process, or the like, or anycombination thereof. In some embodiments, the controller 120 may controlthe data processing system 130 to select different algorithms to processthe raw data of an image.

The data processing system 130 may process information received from theimaging device 110, the controller 120, the input/output device 140,and/or the terminal 170. In some embodiments, the data processing system130 may reconstruct a CT image and/or a PET image based on theinformation acquired by the imaging device 110. The data processingsystem 130 may deliver the images to the input/output device 140 fordisplay. In some embodiments, the data processing system 130 may performoperations including, for example, data preprocessing, imagereconstruction, image correction, image composition, lookup tablecreation, or the like, or any combination thereof. In some embodiments,the data processing system 130 may process data based on an algorithmincluding, for example, the Fourier slice theorem, a filtered backprojection algorithm, fan-beam reconstruction, iterative reconstruction,or the like, or any combination thereof. Merely by way of example, imagedata regarding a lung may be processed in the data processing system130. In some embodiments, the data processing system 130 may generate areconstructed PET image based on a CT image. In some embodiments,artifacts may appear in the PET image because of a mismatch of the PETdata and CT data. The data processing system 130 may apply variousalgorithms or techniques to reduce the artifacts. For example, theprojection data relating to the chest of the object may be processed toreduce the artifacts.

In some embodiments, the data processing system 130 may generate acontrol signal relating to the configuration of the imaging device 110.In some embodiments, the result generated by the data processing system130 may be provided to other modules or units in the system including,e.g., the storage 190, a terminal 170, via the network 160.

The input/output device 140 may receive or output information. In someembodiments, an image 150 such as a CT image and/or a PET imagegenerated by the data processing system 130 may be displayed on theinput/output device 140. In some embodiments, the input/output device140 may include a keyboard, a touch screen, a mouse, a remotecontroller, or the like, or any combination thereof. The input and/oroutput information may take the form of a program, software, analgorithm, data, text, a number, an image, voice, or the like, or anycombination thereof. For example, a user may input some initialparameters or conditions to initiate an imaging process. As anotherexample, some information may be imported from an external resourceincluding, for example, a floppy disk, a hard disk, a wired terminal, awireless terminal, or the like, or any combination thereof. The outputinformation may be transmitted to a display device, a printer, a storagedevice, a computing device, or the like, or a combination thereof. Insome embodiments, the input/output device 140 may include a graphicaluser interface. The graphical user interface may facilitate a user toinput parameters, and/or intervene in a data processing procedure.

The network 160 may include any suitable network that can facilitate theexchange of information and/or data for the imaging system 100. In someembodiments, one or more components of the imaging system 100 (e.g., theimaging device 110, the controller 120, the data processing system 130,the input/output device 140, and/or the terminal 170, etc.) maycommunicate information and/or data with one or more other components ofthe imaging system 100 via the network 160. For example, the dataprocessing system 130 may obtain image data from the imaging device 110via the network 160. As another example, the data processing system 130may obtain user instructions from the terminal 170 via the network 160.

The network 160 may be and/or include a public network (e.g., theInternet), a private network (e.g., a local area network (LAN), a widearea network (WAN)), etc.), a wired network (e.g., an Ethernet network),a wireless network (e.g., an 802.11 network, a Wi-Fi network, etc.), acellular network (e.g., a Long Term Evolution (LTE) network), a framerelay network, a virtual private network (“VPN”), a satellite network, atelephone network, routers, hubs, switches, server computers, and/or anycombination thereof. Merely by way of example, the network 160 mayinclude a cable network, a wireline network, a fiber-optic network, atelecommunications network, an intranet, a wireless local area network(WLAN), a metropolitan area network (MAN), a public telephone switchednetwork (PSTN), a Bluetooth™ network, a ZigBee™ network, a near fieldcommunication (NFC) network, or the like, or any combination thereof. Insome embodiments, the network 160 may include one or more network accesspoints. For example, the network 160 may include wired and/or wirelessnetwork access points such as base stations and/or internet exchangepoints through which one or more components of the imaging system 100may be connected to the network 160 to exchange data and/or information.

The terminal(s) 170 may include a mobile device 171, a tablet computer172, a laptop computer 173, or the like, or any combination thereof. Insome embodiments, the mobile device 171 may include a smart home device,a wearable device, a virtual reality device, an augmented realitydevice, or the like, or any combination thereof. In some embodiments,the smart home device may include a smart lighting device, a controldevice of an intelligent electrical apparatus, a smart monitoringdevice, a smart television, a smart video camera, an interphone, or thelike, or any combination thereof. In some embodiments, the wearabledevice may include a bracelet, footgear, eyeglasses, a helmet, a watch,clothing, a backpack, a smart accessory, or the like, or any combinationthereof. In some embodiments, the mobile device 171 may include a mobilephone, a personal digital assistant (PDA), a gaming device, a navigationdevice, a point of sale (POS) device, a laptop, a tablet computer, adesktop, or the like, or any combination thereof. In some embodiments,the virtual reality device and/or the augmented reality device mayinclude a virtual reality helmet, virtual reality glasses, a virtualreality patch, an augmented reality helmet, augmented reality glasses,an augmented reality patch, or the like, or any combination thereof. Forexample, the virtual reality device and/or the augmented reality devicemay include a Google Glass™, an Oculus Rift™, a Hololens™, a Gear VR™,etc. In some embodiments, the terminal(s) 170 may be part of orcommunicate with the data processing system 130.

The gating system 180 may collect information relating to, for example,breathing, heartbeat, etc. The gating system 180 may analyze theinformation to obtain a motion signal including, for example, arespiration signal, a cardiac motion signal, etc. The gating system 180may include a gating camera for detecting a motion of the subject, acontrol panel, a marker on a surface of the subject for indicating amotion of the subject, or the like, or any combination thereof. In someembodiments, the gating camera may be an infrared camera. For example,when the imaging device 110 is scanning a patient, the gating system maybe triggered automatically. The gating system 180 may collectinformation associated with the respiration motion of the subject duringthe scanning. The data collected by the gating system 180 may be storedtogether with the PET data or CT data.

In some embodiments, the imaging device 110, the controller 120, thedata processing system 130, the input/output device 140, the terminal170, and the gating system 180 may be connected to or communicate witheach other directly. In some embodiments, the imaging device 110, thecontroller 120, the data processing system 130, the input/output device140 may be connected to or communicate with each other via a network160. In some embodiments, the imaging device 110, the controller 120,the data processing system 130, the input/output device 140 may beconnected to or communicate with each other via an intermediate unit(not shown in FIG. 1). The intermediate unit may be a visible componentor an invisible field (radio, optical, sonic, electromagnetic induction,etc.). The connection between different units may be wired or wireless.The wired connection may include using a metal cable, an optical cable,a hybrid cable, an interface, or the like, or any combination thereof.The wireless connection may include using a Local Area Network (LAN), aWide Area Network (WAN), a Bluetooth, a ZigBee, a Near FieldCommunication (NFC), or the like, or any combination thereof. Thenetwork 160 may be used in connection with the present system describedherein are not exhaustive and are not limiting.

The storage 190 may store information related to the imaging system 100.In some embodiments, the storage 190 may perform some storage-relatedfunction, such as data consolidation and/or data pre-processing. Thestorage 190 may acquire information from or output information to othermodules. The information stored in storage 190 may be acquired from oroutput to an external resource, such as a floppy disk, a hard disk, aCD-ROM, a network server, a cloud server, a wireless terminal, or thelike, or any combination thereof.

The storage 190 may store information by way of electric, magnetic,optical energy, or virtual storage resources, etc. The storage modulethat stores information by way of electric energy may include RandomAccess Memory (RAM), Read Only Memory (ROM), flash memory, or the like,or any combination thereof. The storage module that stores informationby way of magnetic energy may include a hard disk, a floppy disk, amagnetic tape, a magnetic core memory, a bubble memory, a USB flashdrive, or the like, or any combination thereof. The storage module thatstores information by way of optical energy may include CD (CompactDisk), VCD (Video Compact Disk), or the like, or any combinationthereof. The storage module that stores information by way of virtualstorage resources may include cloud storage, a virtual private network,and/or other virtual storage resources. The method to store informationmay include sequential storage, link storage, hash storage, indexstorage, or the like, or any combination thereof.

It should be noted that the above description of the imaging system 100is merely an example, and should not be understood as the onlyembodiment. To those skilled in the art, after understanding the basicprinciples of the connection between different units, the units andconnection between the units may be modified or varied without departingfrom the principles. The modifications and variations are still withinthe scope of the current application described above. In someembodiments, these units may be independent, and in some embodiments,part of the units may be integrated into one unit to work together. Insome embodiments, the imaging device 110 may be used in internalinspection of components including e.g., flaw detection, securityscanning, failure analysis, metrology, assembly analysis, void analysis,wall thickness analysis, or the like, or any combination thereof.

FIG. 2 is a schematic diagram illustrating exemplary hardware andsoftware components of a computing device 200 on which data processingsystem 130 or a portion thereof may be implemented according to someembodiments of the present disclosure. For example, the processingsystem 130 or the processing module 440 of the processing system 130 maybe implemented on the computing device 200 and configured to performfunctions of the data processing system 130 described in thisdisclosure.

The computing device 200 may be a general-purpose computer or a specialpurpose computer, both may be used to implement an imaging processingsystem for the present disclosure. The computing device 200 may be usedto implement any component for image processing as described herein. Forexample, the data processing system 130 may be implemented on thecomputing device 200, via its hardware, software program, firmware, orany combination thereof. Although only one such computer is shown, forconvenience, the computer functions relating to the image processing asdescribed herein may be implemented in a distributed fashion on a numberof similar platforms, to distribute the processing load.

The computing device 200, for example, may include communication (COMM)ports 260 connected to and from a network to facilitate datacommunications. The computing device 200 may also include a processor230 (e.g., a central processing unit (CPU)), in the form of one or moreprocessors, for executing program instructions. The exemplary computerplatform may include an internal communication bus 220, program storageand data storage of different forms, for example, a disk 210, and a readonly memory (ROM) 240, or a random-access memory (RAM) 250, for variousdata files to be processed and/or transmitted by the computer. Theexemplary computer platform may also include program instructions storedin the ROM 240, RAM 250, and/or another type of non-transitory storagemedium to be executed by the processor 230. The methods and/or processesof the present disclosure may be implemented as the programinstructions. The computing device 200 also includes an I/O component270, supporting input/output between the computer and other componentstherein such as user interface elements 280. The computing device 200may also receive programming and data via network communications.

Merely for illustration, only one processor is illustrated in thecomputing device 200. However, it should be noted that the computingdevice 200 in the present disclosure may also include multipleprocessors, thus operations and/or method steps that are performed byone processor as described in the present disclosure may also be jointlyor separately performed by the multiple processors. For example, if inthe present disclosure the processor of the computing device 200executes both operation A and operation B, it should be understood thatoperation A and operation B may also be performed by two differentprocessors jointly or separately in the computing device 200 (e.g., thefirst processor executes operation A and the second processor executesoperation B, or the first and second processors jointly executeoperations A and B).

FIG. 3 is a schematic diagram illustrating exemplary hardware and/orsoftware components of an exemplary mobile device 300 on which aterminal 170 may be implemented according to some embodiments of thepresent disclosure. As illustrated in FIG. 3, the mobile device 300 mayinclude a communication platform 310, a display 320, a graphicprocessing unit (GPU) 330, a central processing unit (CPU) 340, an I/O350, a memory 360, an operation system (OS) 370, applications 380, andstorage 390. In some embodiments, any other suitable component,including but not limited to a system bus or a controller (not shown),may also be included in the mobile device 300. In some embodiments, amobile operating system 370 (e.g., iOS™, Android™, Windows Phone™, etc.)and one or more applications 380 may be loaded into the memory 360 fromthe storage 390 in order to be executed by the CPU 340. The applications380 may include a browser or any other suitable mobile apps forreceiving and rendering information relating to image processing orother information from the data processing system 130. User interactionswith the information stream may be achieved via the I/O 350 and providedto the data processing system 130 and/or other components of the imagingsystem 100 via the network 160.

FIG. 4 is a block diagram illustrating an exemplary data processingsystem 130 according to some embodiments of the present disclosure. Asshown in FIG. 4, the data processing system 130 may include a dataacquisition module 410, a storage module 420, a display module 430, anda processing module 440. At least a portion of the data processingsystem 130 may be implemented on the computing device 200 as illustratedin FIG. 2, or the mobile device 300 as illustrated in FIG. 3.

The data acquisition module 410 may acquire data. The data may beacquired from one or more components of the imaging system 100, such asthe imaging device 110 and/or the controller 120. In some embodiments,the data may be acquired from an external data source via the network160. The data acquired may be 4D image data, 3D image data, and/or 2Dimage data. The data acquired may include information regarding a wholehuman body, a lung, a bronchus, a thorax, or the like, or anycombination thereof. In some embodiments, the data acquisition module410 may include a wireless receiver to receive data via the network 160.

The storage module 420 may store data. The data stored may be anumerical value, a signal, an image, information of a subject, aninstruction, an algorithm, or the like, or a combination thereof. Thedata stored may be acquired by the data acquisition module 410, importedvia the input/output device 140, generated in the processing module 440,or pre-stored in the storage module 420 during system initialization orbefore an operation of data processing. The storage module 420 mayinclude a system storage device (e.g., a disk) that is providedintegrally (i.e. substantially non-removable), or a storage device thatis removable connectable to the system via, for example, a port (e.g., aUBS port, a firewire port, etc.), a drive (a disk drive, etc.), etc. Thestorage module 420 may include, for example, a hard disk, a floppy disk,selectron storage, random access memory (RAM), dynamic random accessmemory (DRAM), static random access memory (SRAM), bubble memory, thinfilm memory, magnetic plated wire memory, phase change memory, flashmemory, a cloud disk, or the like, or a combination thereof. The storagemodule 420 may be connected to or communicate with one or more of thedata acquisition module 410, the processing module 440, and the displaymodule 430. In some embodiments, the storage module 420 may beoperationally connected with one or more virtual storage resources(e.g., cloud storage, a virtual private network, other virtual storageresources, etc.) via the network 160.

The display module 430 may display information. The informationdisplayed may include a value, a text, an image, and information of asubject. The information displayed may be transmitted from the dataacquisition module 410, the storage module 420, and/or the processingmodule 440. In some embodiments, the display module 430 may transforminformation to the input/output device 140 for display. In someembodiments, the display module 430 may transform the image data that isgenerated from the processing module 440 for display. In someembodiments, the display module 430 may transform the image datadirectly retrieved from the storage module 420 or from an external datasource via the network 160 for display.

The processing module 440 may process data and generate an image. Thedata may be acquired from the data acquisition module 410, the storagemodule 420, etc. The image may be transmitted by the processing module440 to the display module 430. In some embodiments, the data processedmay be acquired from an external data source via the network 160. Insome embodiments, the processing module 440 may reconstruct image datato generate one or more images. In some embodiments, the processingmodule 440 may segment an image.

In some embodiments, the processing module 440 may include a universalprocessor, e.g., a programmable logic device (PLD), anapplication-specific integrated circuit (ASIC), a microprocessor, asystem on chip (SoC), a digital signal processor (DSP), or the like, orany combination thereof. Two or more of these universal processors inthe processing module 440 may be integrated into a hardware device, ortwo or more hardware devices independently with each other. It should beunderstood, the universal processor in the processing module 440 may beimplemented via various configurations. For example, in someembodiments, the processing procedure of the processing module 440 maybe implemented by hardware, software, or a combination of hardwaresoftware, not only by a hardware circuit in a programmable hardwaredevice in an ultra large scale integrated circuit, a gate array chip, asemiconductor such a transistor, or a field programmable gate array, aprogrammable logic device, and also by a software performed by variousprocessors, and also by a combination of the hardware and the softwareabove (e.g., firmware).

It should be noted that the above description of the data processingsystem 130 is merely an example, and should not be understood as theonly embodiment. To those skilled in the art, after understanding thebasic principles of the connection between different units, the unitsand connection between the units may be modified or varied withoutdeparting from the principles. The modifications and variations arestill within the scope of the current application described above. Forexample, the display module 430 may be omitted.

FIG. 5 is a block diagram illustrating an exemplary processing module440 according to some embodiments of the present disclosure. Theprocessing module 440 may include a gating unit 510, a reconstructionunit 520, an image segmentation unit 530, a respiratory phasedetermination unit 540, a motion vector field determination unit 550,and a transformation unit 560.

In some embodiments, the processing module 440 may be implemented on theprocessor 230 in the computing device 200, the CPU 340 in the mobiledevice 300, or any component of the imaging system 100. At least aportion of the processing module 440 may be implemented on the computingdevice 200 as illustrated in FIG. 2 or the mobile device 300 asillustrated in FIG. 3. A module may be a hardware circuit that isdesigned to perform one or more of the following actions, a set ofinstructions stored in one or more storage media, and/or any combinationof the hardware circuit and the one or more storage media.

The gating unit 510 may gate (or bin) PET data into a plurality ofgroups or phase frames of gated PET data. The PET data may be theprojection data of a PET scanning. For example, the PET data may begenerated by scanning the thorax of a patient using the imaging system100 (e.g., a PET imaging system). The PET data may be obtained from theacquisition module 410, or any other components of the imaging system100. In some embodiments, the PET data may be transmitted or received inthe form of an electronic signal. The electronic signal may be used toencode the PET data. Merely by way of example, the PET data may beretrieved from a cloud storage (e.g., a public cloud) via the network160.

In some embodiments, the PET data may correspond to CT data or a CTimage. For instance, the PET data and the CT data and/or CT image may beobtained by scanning a same region of a same subject (for example, apatient). The CT data may be obtained by scanning a patient before orafter a PET scanning of the patient at (essentially) the same patientposition. As used herein, a patient position may refer to a position ofa subject on a table (e.g., the table 114) during a scan (e.g., a CTscan and/or a PET scan).

In some embodiments, the PET data may be gated or binned based on agating condition. In some embodiments, the gating condition may beassociated with a type of motion of the subject (or referred to as asubject motion). The subject motion may include a respiratory motion (orreferred to as a respiration motion) with a plurality of respiratoryphases (related description may be found elsewhere in the presentdisclosure), a cardiac motion with a plurality of cardiac phases, agastrointestinal motion with a plurality of gastrointestinal phases, askeletal muscle motion with a plurality of skeletal muscle motionphases, or the like, or any combination thereof. For example, thesubject (e.g., a patient) may undergo respiratory motion during a PETscanning and/or a CT scanning. The methods and systems are describedwith reference to a respiratory motion for illustrated purposes, and notintended to limit the scope of the present disclosure. The systems andmethods disclosed herein may be applied in the context of other motiontypes including, for example, cardiac motion, gastrointestinal motion,skeletal muscle motion, etc., or a combination thereof.

The gating condition may include a gating parameter, a time interval, aregion of interest, a compression algorithm, or the like, or anycombination thereof. The gating parameter may include a respiratoryphase, a cardiac phase, a gastrointestinal phase, a skeletal musclemotion phase, or the like, or any combination thereof. The respiratoryphase may correspond to the respiratory motion of the subject (e.g., thepatient). The respiratory motion of the subject may include an inhalingphase (or referred to as an inspiratory phase) and/or an exhaling phase(or referred to as an expiratory phase). For example, in the inhalingphase, the patient may expand his/her chest to cause a negative pressurein the chest. The negative pressure may cause the air to flow into thelungs of the patient. As another example, in the exhaling phase, thepatient may shrink the chest to cause a positive pressure in the chest.The positive pressure may push the air out of the lungs.

In some embodiments, the gating unit 510 may gate the PET data bydividing the PET data into a plurality of groups or frames based on atime interval associated with a respiratory motion. The time intervalmay be determined based on the amplitudes of the respiratory motion, thevariation of the amplitudes with time, etc. For example, in arespiratory cycle, from an end-expiration to an end-inspiration, themotion amplitude may increase from a lowest value to a highest value. Anaverage value of the lowest value and the highest value may bedetermined to be a midway amplitude. In this case, a first time intervalmay be determined to be the time period between the time pointcorresponding to an end-expiration and the time point corresponding tothe midway amplitude that first appears during the respiration motionafter the end-expiration. A second time interval may be determined to bethe time period between the time point corresponding to the timing ofthe midway amplitude and the time point corresponding to theend-inspiration that first appears during the respiration motion afterthe midway amplitude. Similarly, the number of groups may vary, a groupof PET data corresponding to a time interval that in turn corresponds toa range of respiratory motion amplitudes of the subject. In someembodiments, the time interval may be a constant.

In some embodiments, the gating unit 510 may divide the PET data basedon the motion information acquired by the gating system 180. The gatingsystem 180 may include a device for detecting a motion of the subject, acontrol panel, a marker on a surface of the subject for indicating amotion of the subject, or the like, or any combination thereof. In someembodiments, the gating system 180 may include a motion detectiondevice, such as a gating camera (e.g., an infrared camera), a beltsecured around the chest of the subject, or another pressure measurementtechnique or device to measure the change of pressure during thebreathing cycles of the subject. The gating system 180 may be used tocollect information relating to, for example, respiration, heartbeat,etc. The gating system 180 may analyze the information to obtain thegating parameter (e.g., the respiratory phase). In some embodiments,motion information may be derived from the imaging data including, forexample, PET data. Exemplary gating techniques, including self-gating,may be found in, for example, U.S. application Ser. No. 15/386,048 filedDec. 21, 2016 and Ser. No. 15/616,425 filed Jun. 9, 2017, both entitled“METHODS AND SYSTEMS FOR EMISSION COMPUTED TOMOGRAPHY IMAGERECONSTRUCTION,” the contents of each of which are hereby incorporatedby reference.

The reconstruction unit 520 may reconstruct one or more gated PET imagesbased on the gated PET data corresponding to different respiratoryphases. Additionally or alternatively, the reconstruction unit 520 mayreconstruct an attenuation corrected PET image corresponding to arespiratory phase based on the gated PET data and a CT image (or arespiratory phase-matched CT image as described elsewhere in the presentdisclosure) corresponding to the respiratory phase. In some embodiments,the attenuated corrected gated PET image may integrate information ofthe gated PET data and the CT image (or the respiratory phase-matched CTimage). The anatomical information of the subject may be obtained fromthe CT image (or the respiratory phase-matched CT image), and thefunctional information may be obtained from the gated PET data. Thereconstruction unit 520 may generate an attenuation map including aplurality of attenuation coefficients based on the CT image (or therespiratory phase-matched CT image). The attenuation map may be used tocorrect the gated PET data. The reconstruction unit 520 may thenreconstruct an attenuated corrected PET image corresponding to therespiratory phase based on the gated PET data and the correspondingattenuation map.

In some embodiments, the reconstruction unit 520 may use areconstruction algorithm to reconstruct a gated PET image and/or a PETimage. Exemplary reconstruction algorithms may include amaximum-likelihood reconstruction of attenuation and activity (MLAA)algorithm, an iterative reconstruction algorithm (e.g., a statisticalreconstruction algorithm), a Fourier slice theorem algorithm, a filteredback projection (FBP) algorithm, a compressed sensing (CS) algorithm, afan-beam reconstruction algorithm, a maximum likelihood expectationmaximization (MLEM) algorithm, an ordered subset expectationmaximization (OSEM) algorithm, a maximum a posterior (MAP) algorithm, ananalytic reconstruction algorithm, or the like, or any combinationthereof.

The image segmentation unit 530 may segment an image. For example, theimage segmentation unit 530 may identify one or more VOIs or sub-regionsin a CT image by segmenting the CT image. In some embodiments, the imagesegmentation unit 530 may segment an image based on an imagesegmentation technique. Exemplary image segmentation techniques mayinclude an edge detection technique, a threshold segmentation technique,a histogram-based segmentation technique, a clustering segmentationtechnique, a compression-based segmentation technique, a region-growingsegmentation technique, a graph partitioning technique, or the like, ora combination thereof. In some embodiments, the edge detection techniquemay be performed based on an edge detection algorithm, for example, aSobel edge detection algorithm, a Canny edge detection algorithm, aphase congruency-based algorithm, or the like, or a combination thereof.

The respiratory phase determination unit 540 may determine a respiratoryphase of a CT image. In some embodiments, the respiratory phase of theCT image may be determined based on a plurality of gated PET images thatcorresponds to a same scanning region of a subject as the CT image. Thegated PET images may correspond to a plurality of respiratory phases.The respiratory phase determination unit 540 may determine a referencerespiration phase of the CT image among the respiratory phases of thegated PET images. The reference respiratory phase may be designated asthe respiratory phase of the CT image. The reference respiration phasemay be any one of the respiratory phases of the gated PET images. Insome embodiments, the reference respiration phase may be determinedbased on similarities between the CT image (or a portion thereof) andthe gated PET images (or a portion thereof). In some embodiments, thesimilarity may include a pixel-based similarity, an entropy-basedsimilarity, a mutual information similarity, or the like, or anycombination thereof.

The motion vector field determination unit 550 may determine a motionvector field between two images by registering the two images. Forexample, the motion vector field determination unit 550 may register twogated PET images corresponding to different respiratory phases. In someembodiments, the motion vector field determination unit 550 may registerone or more gated PET images with a reference gated PET image. Thereference gated PET image may be one of the gated PET imagescorresponding to a reference respiratory phase of a CT image.

The registration may be implemented based on at least one registrationalgorithm. Exemplary registration algorithms may include a point-basedregistration algorithm (e.g., an anatomic-landmark-based registrationalgorithm), a curve-based registration algorithm, a surface-basedregistration algorithm (e.g., an surface-profile-based surface profile),a spatial alignment registration algorithm, a cross-correlationregistration algorithm, a mutual-information-based registrationalgorithm, a sequential similarity detection algorithm (SSDA), anonlinear transformation registration algorithm, an optical flow, demonsregistration algorithm, B-spline registration algorithm, or the like, orany combination thereof. In some embodiments, the registration may beperformed based on a rigid transformation, an affine transformation, aprojection transformation, a nonlinear transformation, anoptical-flow-based registration, a similarity measurement, or the like,or any combination thereof. The similarity measurement may include amutual-information-based measurement, a Fourier-analysis-basedmeasurement, or the like, or any combination thereof.

In some embodiments, the motion vector field determination unit 550 maydetermine a motion vector field between two gated PET imagescorresponding to different respiratory phases. The motion vector fieldmay include a plurality of motion vectors. A motion vector may be usedto describe the motion of a spatial point of the subject between tworespiratory phases corresponding to the two gated PET images. In someembodiments, a motion vector may be determined by registering the twogated PET images. For example, after the two gated PET images areregistered, locations of two voxels in the gated PET imagescorresponding to a same spatial point of the subject may be determined.Then the motion vector field determination unit 550 may determine thecorresponding motion vector of the spatial point based on the locationsof the two voxels. A motion vector field may include a portion or all ofthe motion vectors between two gated PET images. The motion vector fieldmay be used to describe a motion relationship of spatial points betweentwo respiration phases corresponding to the two gated PET images.

The transformation unit 560 may transform an image or a portion thereofbased on a motion vector field. For example, the transformation unit 560may transform a CT image of a first respiratory phase (e.g., a referencerespiratory phase) based on a motion vector field between the firstrespiratory phase and a second respiratory phase. The transformed CTimage may be regarded as a respiratory phase-matched CT imagecorresponding to the second respiratory phase. In some embodiments, thetransformation unit 560 may transform a VOI in the CT image of asubject. The VOI to be corrected may correspond to, for example, aportion of the scanning region of the CT image that excludes one or morebones of the subject. In some embodiments, the VOI to be corrected maycorrespond to at least part of a thoracic and abdominal region of thesubject.

It should be noted that the above descriptions of the processing module440 are merely provided for the purposes of illustration, and notintended to limit the scope of the present disclosure. For personshaving ordinary skills in the art, multiple variations and modificationsmay be made under the teachings of the present disclosure. However,those variations and modifications do not depart from the scope of thepresent disclosure. In some embodiments, two or more units may beintegrated into one unit to perform the functions thereof.

FIG. 6 is a flowchart illustrating an exemplary process forreconstructing an attenuation corrected PET image corresponding to atarget respiratory phase according to some embodiments of the presentdisclosure. At least a portion of process 600 may be implemented on thecomputing device 200 as illustrated in FIG. 2 or the mobile device 300as illustrated in FIG. 3. In some embodiments, one or more operations ofprocess 600 may be implemented in the imaging system 100 as illustratedin FIG. 1. For example, the process 600 may be stored in the storagemodule 420 of the data processing system 130 in the form ofinstructions, and invoked and/or executed by the data processing system130 (e.g., the processor 230 of the data processing system 130).

In some embodiments, the attenuation corrected PET image of a subject(e.g., a patient) may be reconstructed based on CT data and PET data ofthe subject. The CT data may be applied in the attenuation correction ofthe PET data. A CT scan usually takes a short time, and a PET scanusually takes a relatively long time. For example, a CT scan may beperformed at a speed of about 1.5 seconds/table position. A PET scan maybe performed at a speed of about 5 minutes/table position. The subjectmay undergo a respiratory motion during the CT scan and/or the PET scan.The CT data may be considered to correspond to a respiratory phasebecause of the short scanning duration. The PET data may correspond to aplurality of respiratory phases, which may lead to a mismatch betweenthe CT data and the PET data. The CT data and the PET data may need tobe matched with respect to their corresponding motion phases to reducemotion artifact due to, e.g., the respiratory motion.

In 602, the acquisition module 410 may obtain a CT image correspondingto a scanning region of a subject. The CT image may correspond to arespiratory phase. The subject may include a patient, an animal, aphantom, or a portion thereof including, for example, an artificiallimb, an artificial heart, a tumor, any structure or organ that may beexamined using X-ray, or the like, or any combination thereof. Thescanning region may include any part of the subject. For example, thescanning region may include a whole body of the subject. Alternatively,the scanning region may be a portion of the subject, such as a brain, alung, a liver, a kidney, a bone, any organ or region of interest (ROI)of the subject. In some embodiments, the scanning region may correspondto at least a portion of a thorax and an abdomen of the subject.

In some embodiments, the CT image may be a 3D CT image including aplurality of 2D CT image layers (e.g., image slices). In someembodiments, the CT image may be a processed CT image (e.g., anattenuation map relating to the CT image). The CT image may be generatedbased on CT data acquired by a CT scanner, or retrieved from a storagedevice via the network 160.

In some embodiments, the CT image may be acquired by a CT scanner with aCT field of view (FOV). The CT FOV may refer to an area scanned by theCT scanner during a CT scan. In some embodiments, the CT image may beacquired when at least a portion of a lung and a portion of a liver ofthe subject are located in a central region of the CT FOV. A portion ofthe subject is considered to be located at the central region of the CTFOV if it is near a central point of the CT FOV (e.g., a central pointof the CT FOV along an axial direction of the CT scanner). The at leasta portion of the lung and a portion of the liver of the subject maycorrespond to one or more sub-regions in the CT image. In someembodiments, at least a portion of the lung and a portion of the liverof the subject may be located within but unnecessarily at the center ofthe CT FOV. For a PEC/CT device, the CT FOV may be larger than the PETFOV (see, e.g., relevant description of operation 604). To match CT data(or image) and PET data (or image) acquired by the PET/CT device withrespect to the same subject (or a portion thereof), the portion of theCT data corresponding to the PET data may be segmented. As used herein,a portion of the CT data (or image) is considered to correspond to thePET data (or image) if they correspond to one or more same spatialpoints of the subject. The segmented portion of the CT data (or image)may further be used in attenuation correction of the PET data (orimage). In some embodiments, the sub-regions in the CT image may serveas a basis for matching the CT data and PET data. When at least aportion of the lung and a portion of the liver are both located in thecentral region of the CT FOV, the CT image may be more useful inrespiratory phase determination compared to CT images containing no lungand/or liver.

In 604, the acquisition module 410 may obtain PET data corresponding tothe same scanning region of the subject. As used herein, a CT image andthe PET data (or a PET image) are considered to correspond to a samescanning region if the scanning region corresponding to the CT data (orthe CT image obtained based on the CT data) at least partially overlapswith the scanning region corresponding to the PET data (or the PET imageobtained based on the PET data). The PET data may correspond to the samescanning region as the CT scanning as described in connection with 602.For example, if a CT scan of a chest of the patient is performed, a PETscan of the chest of the patient may be performed when the patient keepsessentially the same patient position, in order to facilitate thecombination of information of the PET data and the CT data.

In some embodiments, the PET data may be acquired by a PET scanner witha PET FOV. The PET FOV may refer to an area scanned by the PET scannerduring a PET scan. In some embodiments, the PET image may be acquiredwhen at least a portion of a lung and a portion of a liver of thesubject are located in a central region of the PET FOV. As such, thereconstructed PET image containing at least a portion of the lung and aportion of the liver may be more helpful in respiratory phasedetermination than the PET image (or a gated PET image) containing noliver or lung.

In 606, the gating unit 510 may gate the PET data into a plurality ofbins corresponding to different respiratory phases of the subject. Thereconstruction unit 520 may reconstruct a plurality of gated PET imagescorresponding to the respiratory phases based on the gated PET data. Forexample, the respiratory phases of the subject may include anintermediate inspiratory phase, an end-inspiratory phase, anintermediate expiratory phase, an end-expiratory phase, or the like, orany combination thereof. The gated PET images may include a gated PETimage corresponding to the intermediate inspiratory phase, a gated PETimage corresponding to the end-inspiratory phase, a gated PET imagecorresponding to the intermediate expiratory phase, a gated PET imagecorresponding to the end-expiratory phase, or the like, or anycombination thereof.

In some embodiments, the gating unit 510 may gate the PET data accordingto a respiration signal of the subject during the PET scan. Therespiration signal may be determined based on the PET data by the gatingunit 510, and/or be acquired from another resource (e.g., the gatingsystem 180). The gating unit 510 may divide the respiratory signal intoa plurality of respiratory phases based on the amplitude or the time ofthe respiratory signal. The gating unit 510 may also determine aplurality of groups (or referred to as frames) of gated PET datacorresponding to the respiratory phases. The reconstruction module 530may reconstruct a plurality of gated PET images based on the gated PETdata corresponding to the respiratory phases. More descriptionsregarding the gating of the PET data and/or the reconstruction of thegated PET images may be found elsewhere in the present disclosure. See,e.g., FIG. 7 and the relevant descriptions thereof.

In 608, the image segmentation unit 530 may identify one or moresub-regions in the CT image. A sub-region in the CT image may includeany portion of the CT image. A sub-region may have any size and/orshape. Different sub-regions may have the same or different sizes and/orshapes. In some embodiments, the image segmentation unit 530 mayidentify a sub-region in the CT image based on an image segmentationtechnique. Exemplary image segmentation techniques may include an edgedetection technique, a threshold segmentation technique, ahistogram-based segmentation technique, a clustering segmentationtechnique, a compression-based segmentation technique, a region-growingsegmentation technique, a graph partitioning technique, or the like, ora combination thereof.

In some embodiments, the one or more sub-regions may correspond to atleast a portion of a lung and at least a portion of a liver of thesubject, and the sub-regions may be smaller than the scanning region.The lung and the liver of the subject have very different attenuationcoefficients. If the respiratory motions of the PET data and the CTimage are mismatched, the lung and the liver in the CT may have be anobvious or visible shift or mismatch with respect to same portions in aPET image (or gated PET image). The sub-regions corresponding to atleast a portion of the lung and a portion of the liver may serve as abasis for matching the PET data and the CT image with respect to theirrespiratory phases.

In some embodiments, the one or more sub-regions may include a firstsub-region corresponding to a left lung of the subject and a secondsub-region corresponding to a right lung of the subject. For brevity,the first sub-region corresponding to the left lung may be referred toas a left sub-region and the second sub-region corresponding to theright lung may be referred to as a right sub-region.

In some embodiments, the image segmentation unit 530 may segment theleft lung and the right lung of the subject from the CT image. The imagesegmentation unit 530 may then determine the left sub-region based onthe left lung and the right sub-region based on the right lung. Thesegmentation of the left lung and/or the right lung may be performedbased on a segmentation technique as described elsewhere in thisdisclosure. For example, the segmentation of the left lung and/or theright lung may be performed based on a region-growing segmentationtechnique and/or a threshold segmentation technique.

For illustration purposes, the determination of the left sub-region isdescribed as an example. After identifying the left lung, the imagesegmentation unit 530 may identify a bottom of the left lung. The bottomof the left lung may border the liver of the subject. Accordingly, thebottom of the left lung may constitute an interface between the leftlung and the liver of the subject. The image segmentation unit 530 mayfurther segment a portion of the liver and/or a portion of the stomachbeneath the bottom of the left lung. The segmented portion of the liverand/or the stomach beneath the bottom of the left lung may have apredetermined thickness. The image segmentation unit 530 may designatethe left lung and the segmented portion of a certain thickness beneaththe bottom of the left lung as the left sub-region.

In 610, the respiratory phase determination unit 540 may determine areference respiratory phase that matches the respiratory phase of the CTimage among the plurality of the respiratory phases of the subject. Thereference respiratory phase may be determined based on the identifiedone or more sub-regions in the CT image and corresponding portions inone or more gated PET images of the plurality of gated PET images. Insome embodiments, the respiratory phase determination unit 540 maydetermine a candidate reference respiratory phase for each sub-region,and determine the reference respiratory phase that matches therespiratory phase of the CT image based on the candidate referencerespiratory phases. More descriptions regarding the determination thereference respiratory phase may be found elsewhere in the presentdisclosure. See, e.g., FIGS. 8A and/or 8B and the relevant descriptionsthereof.

In 612, the motion vector field determination unit 550 may determine amotion vector field corresponding to a target respiratory phase withrespect to the reference respiratory phase relating to the CT image. Thereference respiratory phase relating to the CT image may refer to thereference respiratory phase that matches the respiratory phase of the CTimage as described in connection with 610. The motion vector fieldcorresponding to the target respiratory phase with respect to thereference respiratory phase may refer to a motion vector field between agated PET image corresponding to a target respiratory phase and areference gated PET image. The reference gated PET image may refer tothe gated PET image corresponding to the reference respiratory phase.The reference gated PET image may be reconstructed in 606 or retrievedfrom a storage device in the imaging system 100 (e.g., the storage 190,the storage module 420) or an external storage device via the internet160. The target respiratory phase may be any respiratory phase otherthan the reference respiratory phase.

In some embodiments, the motion vector field determination unit 550 maydetermine the motion vector field by registering the two gated PETimages. For example, the motion vector field determination unit 550 mayregister the two gated PET images based on a registration algorithm.Exemplary registration algorithms may include a point-based registrationalgorithm (e.g., an anatomic-landmark-based registration algorithm), acurve-based registration algorithm, a surface-based registrationalgorithm (e.g., an surface-profile-based surface profile), a spatialalignment registration algorithm, a cross-correlation registrationalgorithm, a mutual-information-based registration algorithm, asequential similarity detection algorithm (SSDA), a nonlineartransformation registration algorithm, an optical flow, or the like, orany combination thereof. In some embodiments, the registration betweenthe two gated PET images may include an automatic registration, asemi-automatic registration, or a manual registration. As used herein,an automatic registration refers to a registration performedautomatically by a computing device (e.g., the computing device 200 asillustrated in FIG. 2) without user intervention. As used herein, asemi-automatic registration refers to a registration performed by acomputing device (e.g., the computing device 200 as illustrated in FIG.2) with user intervention. User intervention may include providinginformation regarding a specific registration algorithm to be used in aregistration, a parameter to be used in a registration, or the like, ora combination thereof. For instance, during a semi-automaticregistration, a user provides information identifying a characteristicfeature (e.g., by marking it on each of the images to be registered on auser interface displaying the images), and a computing device performsthe registration based on the information in combination with aregistration algorithm and/or parameter. As used herein, a manualregistration refers to a registration performed according toinstructions provided by a user. For example, via a user interfaceimplemented on, e.g., an input/output device 140 or a mobile device asillustrated in FIG. 3, a user may align the two gated PET imagesmanually to register the two gated PET images. In some embodiments, theregistration may be performed based on rigid transformation, an affinetransformation, a projection transformation, a nonlinear transformation,an optical-flow-based registration, a similarity measurement, or thelike, or any combination thereof.

The motion vector field may include a plurality of motion vectors. Amotion vector may be used to describe the motion of a spatial point ofthe subject between the gated PET image and the reference respiratoryphase. For example, the motion vector field determination unit 550 maydetermine a first location of a spatial point in the gated PET image tobe (X1, Y1, Z1), and a second location of the point in the referencegated PET image to be (X2, Y2, Z2). The motion vector fielddetermination unit 550 may further determine a motion vector to be (Ux,Uy, Uz) based on the first location and the second location of thespatial point, where Ux may be equal to (X1−X2), Uy may be equal to(Y1−Y2), and Uz may be equal to (Z1−Z2).

In 614, the image segmentation unit 530 may identify a VOI in the CTimage. The VOI may be smaller than the scanning region, and include anyportion of the CT image that needs to be corrected to match the gatedPET image corresponding to the target respiratory phase.

In some embodiments, the PET data may include a first portion and asecond portion. The first portion may be affected more by therespiratory motion of the subject than the second portion. For example,the first portion may correspond to a portion of the scanning regionthat excludes one or more bones of the subject originally included inthe PET data. Merely by way of example, the first portion may correspondto a portion in a thoracic and abdominal region of the subjectsurrounded by the ribs and the spine of the subject, and the ribs andthe spine of the subject may be excluded from the first portion. Thesecond portion may correspond to the portion outside the thoracic andabdominal cavity. As used herein, the thoracic and abdominal region mayrefer to the region including the thoracic and abdominal cavity and themuscle skin of the ribs and the spine surrounding the thoracic andabdominal cavity. When the subject breaths during a scan, the internalorgans within the thoracic and abdominal region may move (the movementmay be referred to as a respiratory motion). The portion outside thethoracic and abdominal cavity may undergo no or little respiratorymotion. Thus, the first portion may be regarded as being affected moreby the respiratory motion than the second portion. The identified VOI inthe CT image may correspond to the first portion of the PET data. Tomatch the PET data and the CT image, the VOI may need to be subject tomotion transformation and the portion outside the VOI may be omittedfrom the motion transformation. More descriptions regarding thedetermination the VOI may be found elsewhere in the present disclosure.See, e.g., FIG. 9 and the relevant descriptions thereof.

In 616, the transformation unit 560 may obtain a respiratoryphase-matched CT image by transforming the VOI in the CT image based onthe motion vector field between the gated PET image and the referencegated PET image. The transformed CT image may have a matched respiratoryphase (e.g., the same respiratory phase or substantially the samerespiratory phase) with the gated PET image. Thus, the transformed CTimage may also be referred to as the respiratory phase-matched CT imagecorresponding to the gated PET image. The motion transformation of theVOI may refer to a transformation of the locations of the voxels in theVOI to reduce the effect of respiratory motions. In the respiratoryphase-matched CT image, the VOI may be transformed and voxels outsidethe VOI may be omitted from the motion transformation and remain theiroriginal locations in the CT image. The motion transformation of the VOImay be performed based on the motion vector field between the referencegated PET image and the gated PET image corresponding to the targetrespiratory phase.

For illustration purposes, the motion vector field between the referencegated PET image and the gated PET image corresponding to the targetrespiratory phase may be expressed as (m_(u)(x, y, z), m_(v)(x, y, z),m_(w)(x, y, z)), where m_(u) represents the motion vector component inthe x axis direction, m_(v) represents the motion vector component inthe y axis direction, m_(w) represents the motion vector component inthe z axis direction. The z-axis may refer to a direction along which anobject is moved into and out of a detection tunnel of an imaging device(e.g., a PET/CT scanner). The x axis and y axis may form an x-y planethat is perpendicular to the z axis as illustrated in FIG. 1. Thetransformation unit 560 may transform the VOI in the CT image togenerate a respiratory phase-matched CT image corresponding to the gatedPET image by applying the motion vector field to the VOI in the CTimage. The transformation of the VOI in the CT image may be performedaccording to Equation (1) below:

C ₂(x,y,z)=C(x+m _(u)(x,y,z),y+m _(v)(x,y,z),z+m _(w)(x,y,z)),  (1)

where C(x, y, z) represents a VOI in the CT image, and C₂(x, y, z)represents the VOI in the respiratory phase-matched CT imagecorresponding to the gated PET image.

In 618, the reconstruction unit 520 may reconstruct an attenuationcorrected PET image corresponding to the target respiratory phase basedon the respiratory phase-matched CT image and the gated PET datacorresponding to the target respiratory phase. In some embodiments, thereconstruction unit 520 may determine tissue attenuation coefficientscorresponding to different portions (e.g., different organs, differenttissues) of the subject based on the respiratory phase-matched CT image.The reconstruction unit 520 may generate an attenuation mapcorresponding to the 511 KeV photon rays (e.g., γ rays) based on thetissue attenuation coefficients. The reconstruction unit 520 may thenperform an attenuation correction on the gated PET image based on theattenuation map. The attenuation correction of the gated PET image basedon the respiratory phase-matched CT image may also be referred to as aphase-matched attenuation correction of the gated PET image (or gatedPET data).

In some embodiments, the reconstruction unit 520 may reconstruct theattenuation corrected PET image corresponding to the target respiratoryphase based on a reconstruction algorithm. Exemplary reconstructionalgorithms may include an iterative reconstruction algorithm (e.g., astatistical reconstruction algorithm), a Fourier slice theoremalgorithm, a filtered back projection (FBP) algorithm, a compressedsensing (CS) algorithm, a fan-beam reconstruction algorithm, a maximumlikelihood expectation maximization (MLEM) algorithm, an ordered subsetexpectation maximization (OSEM) algorithm, a maximum a posterior (MAP)algorithm, an analytic reconstruction algorithm, or the like, or anycombination thereof.

It should be noted that the above descriptions of the process 600 ismerely provided for the purposes of illustration, and not intended tolimit the scope of the present disclosure. For persons having ordinaryskills in the art, multiple variations and modifications may be madeunder the teachings of the present disclosure. However, those variationsand modifications do not depart from the scope of the presentdisclosure.

In some embodiments, one or more operations in the process 600 may beomitted and/or one or more additional operations may be added. Forexample, 608 may be omitted. In 610, the respiratory phase determinationunit 540 may determine the reference respiratory phase that matches therespiratory phase the CT image based on the entire CT image and theplurality of gated PET images. As another example, 614 may be omitted.In 616, the transformation unit 560 may transform the entire CT imagebased on the motion vector field to generate the respiratoryphase-matched CT image.

In some embodiments, operations 612 to 618 may be performed for eachrespiratory phase to generate an attenuation corrected PET imagescorresponding to each respiratory phase. In some embodiments, theprocess 600 may include one or more additional operations to reconstructanother attenuation corrected PET image, such as, an attenuationcorrected reference PET image, an attenuation corrected average PETimage, or the like, or any combination thereof. Exemplary techniques forreconstructing an attenuation corrected PET image may be found in, forexample, U.S. application Ser. No. 15/721,783 filed Sep. 30, 2017,entitled “SYSTEMS AND METHODS FOR POSITRON EMISSION TOMOGRAPHY IMAGERECONSTRUCTION,” the contents of which are hereby incorporated byreference. The respiratory phase-matched CT image may be regarded as acorrected CT image in the U.S. application Ser. No. 15/721,783.

In some embodiments, the process 600 may be performed based on ananatomical image other than the CT image. For example, the attenuationcorrected gated PET image corresponding to the target respiratory phasemay be reconstructed based on PET data and an MR image bothcorresponding to the same scanning region of the subject. The MR imagemay be corrected to provide anatomical data of the subject, which may beapplied in combination with tissue attenuation coefficients of differentportions in an attenuation correction of the PET data. In someembodiments, before operation 608, the MR image may be processed (e.g.,filtered, enhanced) so that the organs and/or tissues, such as thebones, lungs, and liver are easier to identify. Operations 608 to 618may then be performed on the processed MR image to generate theattenuation corrected PET image.

FIG. 7 is a flowchart illustrating an exemplary process for gating PETdata according to some embodiments of the present disclosure. In someembodiments, at least a portion of the process 700 may be implemented onthe computing device 200 as illustrated in FIG. 2 or the mobile device300 as illustrated in FIG. 3. In some embodiments, one or moreoperations of process 700 may be implemented in the imaging system 100illustrated in FIG. 1. For example, the process 700 may be stored in thestorage module 420 of the data processing system 130 in the form ofinstructions, and invoked and/or executed by the data processing system130 (e.g., the processor 230 of the data processing system 130). In someembodiments, the process 700 may be performed to achieve operation 606as described in connection with FIG. 6.

In 710, the gating unit 510 may obtain a respiration signal of thesubject during the scanning. The respiration signal may correspond to aplurality of respiratory phases of the subject. In some embodiments, thegating unit 510 may obtain information of a respiratory signal relatingto a respiratory motion from the PET data, and determine the respiratorysignal of the respiratory motion based on the information.

In some embodiments, the respiration signal may be acquired from asource other than the PET data. For instance, the respiration signal maybe obtained from the gating system 180. The gating system 180 maycollect information such as breathing information, heartbeat informationetc. The gating system 180 may also analyze the information to determineone or more gating parameters (e.g., the respiratory phase) and/orobtain the respiration signal.

In some embodiments, the respiratory signal may be approximated by asine function, a cosine function, a polynomial function, a pulsefunction, or the like, or any combination thereof. In some embodiments,the respiratory signal may be expressed in a two-dimensional coordinatesystem. The two-dimensional coordinate system may include a firstcoordinate axis (or the X axis) representing time, and a secondcoordinate axis (or the Y axis) representing amplitude or value. Forexample, the respiration signal may be approximated by a sine functionin the two-dimensional coordinate. The respiration signal may show theamplitude in the Y axis, and the amplitude may vary depending on thetime in the X axis. In some embodiments, the respiration signal may beapproximated by the sine signal or the cosine signal. The gating unit510 may approximate the respiration signal using, for example, the sinefunction, the cosine function, etc. For example, the respiration signalmay be approximated by Equation (2):

Y=c*sin(aX+b),  (2)

where Y is the amplitude of the respiratory motion, X is the time of therespiratory motion, and a, b, and c are constant parameters.

In some embodiments, the respiratory signal may be divided into aplurality of respiratory phases. For example, the gating unit 510 maydivide the respiratory signal into 4 respiratory phases, each of whichmay correspond to a different part in a cycle of the respiratory signal.In some embodiments, the gating unit 510 may divide the respiratorysignal according to the instruction of a user (e.g., a doctor). The usermay provide his/her instruction via a user interface implemented on,e.g., a mobile device as illustrated in FIG. 3.

In some embodiments, the respiratory signal may be divided according tothe amplitude of the respiratory signal. For example, a cycle of therespiratory signal may be divided based on the amplitude of therespiratory signal. If the amplitude of the respiratory signal issegmented into n parts (e.g., from the maximum amplitude to the minimumamplitude), the n parts of the respiratory signal may correspond to nrespiratory phases. In some embodiments, the respiratory signal may bedivided, based on the time of the respiratory signal, into N parts, andthe N parts may correspond to N respiratory phases. For example, if acycle of the respiratory signal lasts 5 seconds, a cycle of therespiratory signal may be divided according to a time interval (e.g.,0.5 seconds, or 1 second), and this cycle of the respiratory signal maybe divided into N respiratory phases (e.g., 5/0.5 or 10 respiratoryphases, or 5/1 or 5 respiratory phases). Exemplary gating techniques,including self-gating, may be found in, for example, U.S. applicationSer. No. 15/386,048 filed Dec. 21, 2016 and Ser. No. 15/616,425 filedJun. 9, 2017, both entitled “METHODS AND SYSTEMS FOR EMISSION COMPUTEDTOMOGRAPHY IMAGE RECONSTRUCTION,” the contents of which are herebyincorporated by reference.

In 720, the gating unit 510 may gate the PET data into a plurality ofbins based on the plurality of respiratory phases of the respirationsignal. The plurality of bins may correspond to the plurality ofrespiratory phases. For example, the respiratory signal may correspondto N respiratory phases, and the gating unit 510 may gate the PET datainto N groups (or frames) of gated PET data based on the N respiratoryphases. Each group of gated PET data may correspond to a respiratoryphase.

In 730, the reconstruction unit 520 may reconstruct the gated PET datato obtain the plurality of gated PET images corresponding to theplurality of respiratory phases of the subject. In some embodiments, thereconstruction unit 520 may reconstruct a gated PET image for eachrespiratory phase based on the corresponding group of gated PET data.Alternatively, the reconstruction unit 520 may reconstruct one or moregated PET image for a portion of respiratory phases according todifferent situations. For example, the reconstruction unit 520 mayreconstruct a gated PET image corresponding to an intermediateinspiratory phase.

In some embodiments, the reconstruction unit 520 may use areconstruction algorithm to reconstruct a gated PET image. Exemplaryreconstruction algorithms may include a maximum-likelihoodreconstruction of attenuation and activity (MLAA) algorithm, aniterative reconstruction algorithm (e.g., a statistical reconstructionalgorithm), a Fourier slice theorem algorithm, a filtered backprojection (FBP) algorithm, a compressed sensing (CS) algorithm, afan-beam reconstruction algorithm, a maximum likelihood expectationmaximization (MLEM) algorithm, an ordered subset expectationmaximization (OSEM) algorithm, a maximum a posterior (MAP) algorithm, ananalytic reconstruction algorithm, or the like, or any combinationthereof. In some embodiments, the reconstruction unit 520 may generate agated PET image based on the MLAA algorithm.

In some embodiments, the reconstruction unit 520 may correct a gated PETimage based on one or more correction techniques. Exemplary correctiontechniques may include a random correction technique, a scattercorrection technique, a dead time correction technique, or the like, orany combination thereof. In some embodiments, the reconstruction unit520 may correct a gated PET image based on an attenuation correctiontechnique other than a CT-based attenuation correction technique. Forexample, the reconstruction unit 520 may perform an attenuationcorrection of the plurality of gated PET images based on an MLAAalgorithm.

FIG. 8A is a flowchart illustrating an exemplary process for determininga reference respiratory phase that matches the respiratory phase of a CTimage according to some embodiments of the present disclosure. In someembodiments, process 800A may be performed to achieve operation 610 asdescribed in connection with FIG. 6. In some embodiments, at least aportion of the process 800A may be implemented on the computing device200 as illustrated in FIG. 2 or the mobile device 300 as illustrated inFIG. 3. In some embodiments, one or more operations of process 800A maybe implemented in the imaging system 100 illustrated in FIG. 1. Forexample, the process 800A may be stored in the storage module 420 of thedata processing system 130 in the form of instructions, and invokedand/or executed by the data processing system 130 (e.g., the processor230 of the data processing system 130).

In 810, for a sub-region, the respiratory phase determination unit 540may determine a candidate reference respiratory phase of the CT imagebased on the sub-region and corresponding portions in a plurality ofgated PET images. In some embodiments, the respiratory phasedetermination unit 540 may determine similarities between the sub-regionin the CT image and a corresponding portion in each gated PET image. Asused herein, a portion of a gated PET image is considered correspondingto a sub-region of the CT image if the portion of the gated PET imagecorresponds to one or more same spatial points of the subject as thesub-region. The respiratory phase determination unit 540 may determinethe candidate reference respiratory phase corresponding to thesub-region based on the determined similarities. More descriptionsregarding the determination of a candidate reference respiratory phasecorresponding to a sub-region may be found elsewhere in the presentdisclosure. See, e.g., FIG. 8B and the relevant descriptions thereof.The operation 810 may be repeated for each of the one or moresub-regions of the CT image based on the plurality of gated PET images.For each of the one or more sub-regions of the CT image, a candidatereference respiratory phase may be identified.

In 820, the respiratory phase determination unit 540 may designate oneof the candidate reference respiratory phases corresponding to the oneor more sub-regions of the CT image as the reference respiratory phasethat matches the CT image.

In some embodiments, the candidate reference respiratory phasescorresponding to different sub-regions may be the same. The candidatereference respiratory phase may be designated as the referencerespiratory phase.

In some embodiments, the candidate reference respiratory phasescorresponding to different sub-regions may be different from each other.The candidate reference respiratory phase designated as the referencerespiratory phase may be selected from the candidate referencerespiratory phases randomly or according to a selection rule. Forexample, for each of the one or more sub-regions, the respiratory phasedetermination unit 540 may determine similarities between the sub-regionand the corresponding portion in each of the each of the plurality ofgated PET images. The respiratory phase determination unit 540 may thendetermine a variation of the similarities corresponding to each of theone or more sub-regions. The variation of the similarities may beassessed by, for example, a difference between the largest similarityand the smallest similarity among the similarities, a square deviationof the similarities, a standard deviation of the similarities, or thelike, or any combination thereof. According to an exemplary selectionrule, the respiratory phase determination unit 540 may designate thecandidate reference respiratory phase of the sub-region corresponding tothe largest variation of the similarities as the reference respiratoryphase that matches the respiratory phase of the CT image.

For illustration purposes, the determination of a reference respiratoryphase among two candidate reference respiratory phases corresponding toa left sub-region and a right sub-region is described as an example. Theleft sub-region may include to a portion of the left lung and a portionof organs below the left lung of the subject and the right sub-regionmay include a portion of the right lung and a portion of organs belowthe right lung of the subject as described in connection with operation608. The similarities between the left sub-region and the correspondingportion in each of the gated PET images may be determined. The largestsimilarity and the smallest similarity corresponding to the leftsub-region may be denoted as A and B, respectively. The similaritiesbetween the right sub-region and the corresponding portion in each ofthe gated PET images may be determined. The largest similarity and thesmallest similarity corresponding to the right sub-region may be denotedas C and D, respectively. If (A−B)>(C−D), the variation of thesimilarities corresponding to the left sub-region is higher than that ofthe right sub-region, which may indicate a higher signal-to-noise ratiocompared to the determination of a reference respiratory phase based onthe left sub-region. Then the candidate reference respiratory phasecorresponding to the left sub-region may be designated as the referencerespiratory phase. Otherwise, the candidate reference respiratory phasecorresponding to the right sub-region may be designated as the referencerespiratory phase.

FIG. 8B is a flowchart illustrating an exemplary process for determininga candidate reference respiratory phase for a sub-region according tosome embodiments of the present disclosure. In some embodiments, process800B may be performed to achieve operation 810. In some embodiments, atleast a portion of the process 800B may be implemented on the computingdevice 200 as illustrated in FIG. 2 or the mobile device 300 asillustrated in FIG. 3. In some embodiments, one or more operations ofprocess 800B may be implemented in the imaging system 100 illustrated inFIG. 1. For example, the process 800B may be stored in the storagemodule 420 of the data processing system 130 in the form ofinstructions, and invoked and/or executed by the data processing system130 (e.g., the processor 230 of the data processing system 130).

In 830, for each of the plurality of gated PET images, the respiratoryphase determination unit 540 may determine a similarity between asub-region in the CT image and a corresponding portion in the gated PETimage. In some embodiments, the similarity may include a pixel-basedsimilarity, an entropy-based similarity, a mutual informationsimilarity, or the like, or any combination thereof. Merely by way ofexample, the respiratory phase determination unit 540 may determine themutual information similarity between the sub-region in the CT image andthe corresponding portion of a gated PET image based on Equation (3):

MI(C,P _(N))=H(C)+H(P _(N))−H(C,P _(N)),  (3)

where MI(C, P_(N)) represents the mutual information similarity betweenthe sub-region in the CT image and the corresponding portion in thegated PET image, H(C) represents an entropy of the sub-region in the CTimage, H(P_(N)) represents an entropy of the corresponding portion inthe gated PET image, and H(C, P_(N)) represents a joint entropy of thesub-region in the CT image and the corresponding portion of the gatedPET image. When the sub-region in the CT image and the correspondingportion in the gated PET image are irrelevant, the joint entropy may besubstantially the same as or similar to a sum of the entropies of thesub-region of the CT image and the corresponding portion in the gatedPET image. When the sub-region in the CT image and the correspondingportion in the gated PET image are relevant, the joint entropy may becloser to the larger entropy of the entropy of the sub-region of the CTimage and the entropy of the corresponding portion in the gated PETimage. In some embodiments, the entropy of the sub-region in the CTimage H(C), or the entropy of corresponding portion in the gated PETimage H(P_(N)) may be determined according to Equation (4):

H(A)=−∫₀ ^(+∞) p _(A)(v)log(p _(A)(v))dv,  (4)

where p_(A)(v) represent a histogram of the image A (or a portionthereof). The image A may be the sub-region in the CT image or thecorresponding portion in the gated PET image. In some embodiments,p_(A)(v) of the image A may be determined according to Equation (5):

p _(A)(V)=∫∫_(All) ^(δ)(A(x,y)−v)dxdy,  (5)

where A(x, y) represents a pixel value of a pixel (or a voxel value of avoxel) at (x, y) in the image A, v is a gray value, δ represents awindow function centered at 0 (e.g., a Gaussian function with mean 0).In some embodiments, the joint entropy H(C, P_(N)) of the sub-region inthe CT image and the corresponding portion in the gated PET image ofgated N may be determined according to Equation (6):

H(C,P _(N))=−∫∫₀ ^(+∞) p _(C,P) _(N) (v,u)log(p _(C,P) _(N)(v,u))dudv,  (6)

where u represents a pixel value of a pixel (or a voxel value of avoxel) in the sub-region of the CT image, v represents a pixel value ofa corresponding pixel (or a voxel value of a corresponding voxel) in thecorresponding portion in the gated PET image, and p_(C,P) _(N) (v, u) isthe probability of pixel value (u, v) in the combined histogram of thesub-region in the CT image and the corresponding portion in the gatedPET image. A pixel (or voxel) in the gated PET image may be consideredcorresponding to the pixel (or voxel) in the sub-region of the CT imageif they correspond to a same spatial point of the subject. In someembodiments, p_(C,P) _(N) (v, u) may be determined according to Equation(7):

p _(C,P) _(N) (v,u)=∫∫_(Cll) ^(δ)(C(x,y)−v) δ(P _(N)(x,y)−u)dxdy,  (7)

where δ represents a window function centered at 0. In some embodiments,the function δ in Equation (5) and Equation (7) may take the form of theDirac delta function, as determined by Equations (8) and (9):

$\begin{matrix}{{\delta (x)} = \{ \begin{matrix}{{+ \infty},} & {x = 0} \\{0,} & {x \neq 0^{\prime}}\end{matrix} } & (8)\end{matrix}$

which is constrained to satisfy the identity:

∫_(−∞) ^(+∞)δ(x)dx=1.  (9)

In 840, the respiratory phase determination unit 540 may identify ahighest similarity among the determined similarities. In someembodiments, the respiratory phase determination unit 540 may rank thesimilarities, e.g., from the lowest similarity to the highestsimilarity, or vice versa, and identify the highest similarity.

In 850, the respiratory phase determination unit 540 may designate therespiratory phase of the gated PET image with the highest similarity asthe candidate reference respiratory phase of the CT image. For each ofthe one or more sub-regions of the CT image, a candidate referencerespiratory phase may be determined.

FIG. 9 is a flowchart illustrating an exemplary process for determininga VOI in the CT image according to some embodiments of the presentdisclosure. In some embodiments, at least a portion of the process 900may be implemented on the computing device 200 as illustrated in FIG. 2or the mobile device 300 as illustrated in FIG. 3. In some embodiments,one or more operations of process 900 may be implemented in the imagingsystem 100 illustrated in FIG. 1. For example, the process 900 may bestored in the storage module 420 of the data processing system 130 inthe form of instructions, and invoked and/or executed by the dataprocessing system 130 (e.g., the processor 230 of the data processingsystem 130). In some embodiments, the process 900 may be performed toachieve operation 614 as described in connection with FIG. 6.

In 910, the image segmentation unit 530 may segment one or more bonessurrounding the thoracic and abdominal cavity (or a portion thereof) ofthe subject. The one or more bones may include one or more ribs and thespine of the subject. In some embodiments, the image segmentation unit530 may segment the bones based on an image segmentation technique, suchas an edge detection technique, a threshold segmentation technique, ahistogram-based segmentation technique, a clustering segmentationtechnique, or the like, or any combination thereof.

In 920, the image segmentation unit 530 may determine one or more edgepoints of the one or more bones. In some embodiments, the imagesegmentation unit 530 may determine one or more edge points of the boneson the inside wall of the thoracic and cavity (or a portion thereof). Insome embodiments, the image segmentation unit 530 may determine the edgepoints based on an edge detection algorithm, for example, a Sobel edgedetection algorithm, a Canny edge detection algorithm, a phasecongruency-based algorithm, or the like, or any combination thereof.

In 930, the image segmentation unit 530 may determine the VOI in the CTimage based on the one or more edge points. In some embodiments, theimage segmentation unit 530 may generate one or more inner surfaces ofthe thoracic and cavity based on the edge points of the bonessurrounding the thoracic and abdominal cavity of the subject. The imagesegmentation unit 530 may designate a VOI in the CT image enclosed bythe determined surfaces as the VOI. In some embodiments, the surfacesmay be determined based on the edge points according to a surfaceinterpolation algorithm, a surface fitting algorithm, or the like, orany combination thereof.

In some embodiments, the image segmentation unit 530 may generate foursurfaces around the thoracic and cavity based on the edge points of thebones. The VOI enclosed by the four surfaces may be designated as theVOI in the CT image. The four surfaces may include a right surface, aleft surface, a front surface, and a rear surface. The right surface maybe a surface determined based on the edge points of the right ribs. Theleft surface may be a surface determined based on the edge points of theleft ribs. The rear surface may be determined based on the edge pointsof the bones on the back of the subject (i.e., ribs, spine). The subjectmay have no or few bones in the front portion of the abdomen. The upperpart of the front surface may be determined based on the edge points ofthe bones in the front chest of the subject (i.e., ribs, spines). Thelower part of the front surface may be determined based on one or moreprophetic edge points that are determined based on a body surface of thesubject in the front portion of the abdomen of the subject. In someembodiments, the prophetic edge points may be located at a predetermineddistance away from the body surface of the subject in the front portionof the abdomen of the subject.

Examples

The following examples are provided for illustration purposes and notintended to limit the scope of the present disclosure.

FIGS. 10A to 10C illustrate exemplary sub-regions 1010 and 1020 in a CTimage according to some embodiments of the present disclosure. FIGS. 10Ato 10C illustrate a transverse plane, a coronal plane, and a sagittalplane of the sub-regions 1010 and 1020, respectively. The secondsub-region 1010 includes a right lung and the first sub-region 1020includes a left lung. After portions corresponding to the right lung andthe left lung were segmented in the CT image, the portions were extendeddownward toward the liver and the stomach to obtain the sub-regions 1010and 1020. The sub-regions 1010 and 1020 include a portion of the liverand a portion of the stomach of the subject. In some embodiments, thesub-regions 1010 and 1020 may be used in the determination of areference respiratory phase of the CT image.

FIGS. 11A and 11B illustrate exemplary edge points of bones surroundingthe thoracic and cavity of a subject according to some embodiments ofthe present disclosure. The bones surrounding the thoracic and abdominalcavity include ribs 1120 and the spine 1110 of the imaged subject. FIG.11A illustrates edge points of bones on the back of the subject and edgepoints of bones in the front portion of the abdominal cavity. The boneson the back of the subject include the spine 1110 and the ribs 1120.

The subject has no or few bones in the front portion of the abdomen. Theedge points of the front portion of the abdomen are determined based onthe body surface of the subject in the front portion of the abdomen. Theedge points 1130 in the front portion of the abdomen illustrated in FIG.11A were determined to be points located at a predetermined distanceaway from the body surface of the subject in front of the abdomen. FIG.11B illustrates edge points of the left ribs and the right ribs of thesubject.

As described in connection with FIG. 9, one or more surfaces of thethoracic and abdominal cavity in a CT image may be determined based onthe edge points. The one or more surfaces may include a front surface, arear surface, a left surface, and a right surface. A VOI enclosed by thesurfaces may be designated as a VOI in the CT image. FIG. 11Cillustrates an exemplary rear surface of the thoracic and abdominalcavity of a subject that was determined according to some embodiments ofthe present disclosure. FIG. 11D illustrates a front surface 1140 and arear surface 1150 of the thoracic and abdominal cavity of the subjectthat were determined according to some embodiments of the presentdisclosure. FIG. 11E illustrates a transversal plane of the boundary ofan exemplary VOI 1160 in a CT image that was determined according tosome embodiments of the present disclosure. The VOI 1170 may be enclosedby a closed curve 1170. The closed curve 1170 was determined bycombining the front surface, the rear surface, the left surface, and theright surface of the thoracic and abdominal cavity of the subject.

FIGS. 12A to 12C illustrate an exemplary VOI 1210 in a CT image that wasdetermined according to some embodiments of the present disclosure.FIGS. 12A to 12C illustrate a transverse plane, a coronal plane, and asagittal plane of the VOI 1210 in the CT image, respectively. The VOI1210 on the transverse plane is enclosed by a closed curve 1220. The VOI1210 on the coronal plane is enclosed by a closed curve 1230. The VOI1210 on the sagittal plane is enclosed by a closed curve 1240. In someembodiments, the VOI 1210 may be a VOI within a thoracic and abdominalcavity that excludes one or more bones of a subject.

Having thus described the basic concepts, it may be rather apparent tothose skilled in the art after reading this detailed disclosure that theforegoing detailed disclosure is intended to be presented by way ofexample only and is not limiting. Various alterations, improvements, andmodifications may occur and are intended to those skilled in the art,though not expressly stated herein. These alterations, improvements, andmodifications are intended to be suggested by this disclosure, and arewithin the spirit and scope of the exemplary embodiments of thisdisclosure.

Moreover, certain terminology has been used to describe embodiments ofthe present disclosure. For example, the terms “one embodiment,” “anembodiment,” and/or “some embodiments” mean that a particular feature,structure or characteristic described in connection with the embodimentis included in at least one embodiment of the present disclosure.Therefore, it is emphasized and should be appreciated that two or morereferences to “an embodiment” or “one embodiment” or “an alternativeembodiment” in various portions of this specification are notnecessarily all referring to the same embodiment. Furthermore, theparticular features, structures or characteristics may be combined assuitable in one or more embodiments of the present disclosure.

Further, it will be appreciated by one skilled in the art, aspects ofthe present disclosure may be illustrated and described herein in any ofa number of patentable classes or context including any new and usefulprocess, machine, manufacture, or composition of matter, or any new anduseful improvement thereof. Accordingly, aspects of the presentdisclosure may be implemented entirely hardware, entirely software(including firmware, resident software, micro-code, etc.) or combiningsoftware and hardware implementation that may all generally be referredto herein as a “block,” “module,” “module,” “unit,” “component,” or“system.” Furthermore, aspects of the present disclosure may take theform of a computer program product embodied in one or more computerreadable media having computer readable program code embodied thereon.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including electro-magnetic, optical, or thelike, or any suitable combination thereof. A computer readable signalmedium may be any computer readable medium that is not a computerreadable storage medium and that may communicate, propagate, ortransport a program for use by or in connection with an instructionexecution system, apparatus, or device. Program code embodied on acomputer readable signal medium may be transmitted using any appropriatemedium, including wireless, wireline, optical fiber cable, RF, or thelike, or any suitable combination of the foregoing.

Computer program code for carrying out operations for aspects of thepresent disclosure may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C #, VB.NET, Python or the like, conventional procedural programming languages,such as the “C” programming language, Visual Basic, Fortran 2003, Perl,COBOL 2002, PHP, ABAP, dynamic programming languages such as Python,Ruby and Groovy, or other programming languages. The program code mayexecute entirely on the user's computer, partly on the user's computer,as a stand-alone software package, partly on the user's computer andpartly on a remote computer or entirely on the remote computer orserver. In the latter scenario, the remote computer may be connected tothe user's computer through any type of network, including a local areanetwork (LAN) or a wide area network (WAN), or the connection may bemade to an external computer (for example, through the Internet using anInternet Service Provider) or in a cloud computing environment oroffered as a service such as a Software as a Service (SaaS).

Furthermore, the recited order of processing elements or sequences, orthe use of numbers, letters, or other designations therefore, is notintended to limit the claimed processes and methods to any order exceptas may be specified in the claims. Although the above disclosurediscusses through various examples what is currently considered to be avariety of useful embodiments of the disclosure, it is to be understoodthat such detail is solely for that purpose, and that the appendedclaims are not limited to the disclosed embodiments, but, on thecontrary, are intended to cover modifications and equivalentarrangements that are within the spirit and scope of the disclosedembodiments. For example, although the implementation of variouscomponents described above may be embodied in a hardware device, it mayalso be implemented as a software only solution—e.g., an installation onan existing server or mobile device.

Similarly, it should be appreciated that in the foregoing description ofembodiments of the present disclosure, various features are sometimesgrouped together in a single embodiment, figure, or description thereoffor the purpose of streamlining the disclosure aiding in theunderstanding of one or more of the various inventive embodiments. Thismethod of disclosure, however, is not to be interpreted as reflecting anintention that the claimed subject matter requires more features thanare expressly recited in each claim. Rather, inventive embodiments liein less than all features of a single foregoing disclosed embodiment.

In some embodiments, the numbers expressing quantities, properties, andso forth, used to describe and claim certain embodiments of theapplication are to be understood as being modified in some instances bythe term “about,” “approximate,” or “substantially.” For example,“about,” “approximate,” or “substantially” may indicate ±20% variationof the value it describes, unless otherwise stated. Accordingly, in someembodiments, the numerical parameters set forth in the writtendescription and attached claims are approximations that may varydepending upon the desired properties sought to be obtained by aparticular embodiment. In some embodiments, the numerical parametersshould be construed in light of the number of reported significantdigits and by applying ordinary rounding techniques. Notwithstandingthat the numerical ranges and parameters setting forth the broad scopeof some embodiments of the application are approximations, the numericalvalues set forth in the specific examples are reported as precisely aspracticable.

Each of the patents, patent applications, publications of patentapplications, and other material, such as articles, books,specifications, publications, documents, things, and/or the like,referenced herein is hereby incorporated herein by this reference in itsentirety for all purposes, excepting any prosecution file historyassociated with same, any of same that is inconsistent with or inconflict with the present document, or any of same that may have alimiting affect as to the broadest scope of the claims now or laterassociated with the present document. By way of example, should there beany inconsistency or conflict between the descriptions, definition,and/or the use of a term associated with any of the incorporatedmaterial and that associated with the present document, the description,definition, and/or the use of the term in the present document shallprevail.

In closing, it is to be understood that the embodiments of theapplication disclosed herein are illustrative of the principles of theembodiments of the application. Other modifications that may be employedmay be within the scope of the application. Thus, by way of example, butnot of limitation, alternative configurations of the embodiments of theapplication may be utilized in accordance with the teachings herein.Accordingly, embodiments of the present application are not limited tothat precisely as shown and described.

1-30. (canceled)
 31. A method for image processing implemented on atleast one machine, each of which includes a processor and a storagedevice, the method comprising: obtaining an anatomical image andpositron emission tomography (PET) data of a subject, the subjectundergoing a physiological motion; gating the PET data into a pluralityof bins, the plurality of bins corresponding to a plurality of motionphases of the subject; reconstructing, based on the gated PET data, aplurality of gated PET images, each of the plurality of gated PET imagescorresponding to a motion phase of the plurality of motion phases;identifying, in the anatomical image, one or more sub-regions associatedwith the physiological motion of the subject; determining, based on theone or more sub-regions in the anatomical image and the plurality ofgated PET images, a reference motion phase that matches a motion phaseof the anatomical image among the plurality of motion phases; andreconstructing, based on the reference motion phase and the gated PETdata, an attenuation corrected PET image corresponding to a targetmotion phase.
 32. The system of claim 31, wherein the physiologicalmotion of the subject is a respiratory motion, and the one or moresub-regions correspond to at least a portion of a lung and a portion ofa liver.
 33. The method of claim 32, wherein the one or more sub-regionsinclude a first sub-region and a second sub-region, and the identifyingone or more sub-regions in the anatomical image comprises: segmenting aleft lung and a right lung of the subject in the anatomical image;determining the first sub-region based on the left lung; and determiningthe second sub-region based on the right lung.
 34. The method of claim31, wherein the determining a reference motion phase that matches amotion phase of the anatomical image among the plurality of motionphases comprises: for each of the one or more sub-regions, determining,based on the sub-region and corresponding portions in the plurality ofgated PET images, a candidate reference motion phase of the anatomicalimage the among the plurality of motion phases; and designating onecandidate reference motion phase of the candidate reference motionphases as the reference motion phase that matches the motion phase ofthe anatomical image.
 35. The method of claim 34, wherein for asub-region in the anatomical image, the determining a candidatereference motion phase of the anatomical image comprises: for each ofthe plurality of gated PET images, determining a similarity between thesub-region and the corresponding portion in the gated PET image;identifying a highest similarity among the determined similarities; anddesignating the motion phase of the gated PET image with the highestsimilarity as the candidate reference motion phase of the anatomicalimage.
 36. The method of claim 31, wherein the reconstructing anattenuation corrected PET image corresponding to a target motion phasecomprises: determining, based on the gated PET image corresponding tothe target motion phase and the gated PET image corresponding to thereference motion phase, a motion vector field of the target motion phasewith respect to the reference motion phase; obtaining a motionphase-matched anatomical image for the target motion phase bytransforming a volume of interest (VOI) in the anatomical image based onthe motion vector field of the target motion phase with respect to thereference motion phase; and reconstructing, based on the motionphase-matched anatomical image and the gated PET data, the attenuationcorrected PET image corresponding to the target motion phase.
 37. Themethod of claim 36, wherein the PET data includes a first portion and asecond portion, the first portion is affected more by a physiologicalmotion of the subject than the second portion, and the first portioncorresponds to the VOI in the anatomical image.
 38. The method of claim36, wherein the physiological motion of the subject is a respiratorymotion, and the method further comprises segmenting the VOI in theanatomical image, and wherein the segmenting the VOI in the anatomicalimage comprises: segmenting, in the anatomical image, one or more bonessurrounding the thoracic and abdominal cavity of the subject locatedwithin the scanning region; determining one or more edge points of theone or more bones; and determining the VOI based on the one or more edgepoints:
 39. The method of claim 31, wherein the anatomical image is atleast one of a computed tomography (CT) image or a magnetic resonance(MR) image.
 40. The method of claim 31, wherein the PET data is acquiredby a PET scanner with a PET field of view (FOV), and the obtaining ofthe PET data includes: acquiring the PET data by locating the at least aportion of the lung and a portion of the liver of the subject in acentral region of the PET FOV of the PET scanner.
 41. A system,comprising: at least one storage device storing a set of instructionsfor image processing; and at least one processor configured tocommunicate with the at least one storage device, wherein when executingthe set of instructions, the at least one processor is configured todirect the system to perform operations including: obtaining ananatomical image and positron emission tomography (PET) data of asubject, the subject undergoing a physiological motion; gating the PETdata into a plurality of bins, the plurality of bins corresponding to aplurality of motion phases of the subject; reconstructing, based on thegated PET data, a plurality of gated PET images, each of the pluralityof gated PET images corresponding to a motion phase of the plurality ofmotion phases; identifying, in the anatomical image, one or moresub-regions associated with the physiological motion of the subject;determining, based on the one or more sub-regions in the anatomicalimage and the plurality of gated PET images, a reference motion phasethat matches a motion phase of the anatomical image among the pluralityof motion phases; and reconstructing, based on the reference motionphase and the gated PET data, an attenuation corrected PET imagecorresponding to a target motion phase.
 42. The system of claim 41,wherein the physiological motion of the subject is a respiratory motion,and the one or more sub-regions correspond to at least a portion of alung and a portion of a liver.
 43. The system of claim 42, wherein theone or more sub-regions include a first sub-region and a secondsub-region, and the identifying one or more sub-regions in theanatomical image comprises: segmenting a left lung and a right lung ofthe subject in the anatomical image; determining the first sub-regionbased on the left lung; and determining the second sub-region based onthe right lung.
 44. The system of claim 41, wherein the determining areference motion phase that matches a motion phase of the anatomicalimage among the plurality of motion phases comprises: for each of theone or more sub-regions, determining, based on the sub-region andcorresponding portions in the plurality of gated PET images, a candidatereference motion phase of the anatomical image the among the pluralityof motion phases; and designating one candidate reference motion phaseof the candidate reference motion phases as the reference motion phasethat matches the motion phase of the anatomical image.
 45. The system ofclaim 44, wherein for a sub-region in the anatomical image, thedetermining a candidate reference motion phase of the anatomical imagecomprises: for each of the plurality of gated PET images, determining asimilarity between the sub-region and the corresponding portion in thegated PET image; identifying a highest similarity among the determinedsimilarities; and designating the motion phase of the gated PET imagewith the highest similarity as the candidate reference motion phase ofthe anatomical image.
 46. The system of claim 41, wherein thereconstructing an attenuation corrected PET image corresponding to atarget motion phase comprises: determining, based on the gated PET imagecorresponding to the target motion phase and the gated PET imagecorresponding to the reference motion phase, a motion vector field ofthe target motion phase with respect to the reference motion phase;obtaining a motion phase-matched anatomical image for the target motionphase by transforming a volume of interest (VOI) in the anatomical imagebased on the motion vector field of the target motion phase with respectto the reference motion phase; and reconstructing, based on the motionphase-matched anatomical image and the gated PET data, the attenuationcorrected PET image corresponding to the target motion phase.
 47. Thesystem of claim 46, wherein the PET data includes a first portion and asecond portion, the first portion is affected more by a physiologicalmotion of the subject than the second portion, and the first portioncorresponds to the VOI in the anatomical image.
 48. The system of claim46, wherein the physiological motion of the subject is a respiratorymotion, and the method further comprises segmenting the VOI in theanatomical image, and wherein the segmenting the VOI in the anatomicalimage comprises: segmenting, in the anatomical image, one or more bonessurrounding the thoracic and abdominal cavity of the subject locatedwithin the scanning region; determining one or more edge points of theone or more bones; and determining the VOI based on the one or more edgepoints:
 49. The system of claim 41, wherein the anatomical image is atleast one of a computed tomography (CT) image or a magnetic resonance(MR) image.
 50. A non-transitory computer readable medium, comprising aset of instructions for image processing, wherein when executed by atleast one processor, the set of instructions direct the at least oneprocessor to effectuate a method, the method comprising: obtaining ananatomical image and positron emission tomography (PET) data of asubject, the subject undergoing a physiological motion; gating the PETdata into a plurality of bins, the plurality of bins corresponding to aplurality of motion phases of the subject; reconstructing, based on thegated PET data, a plurality of gated PET images, each of the pluralityof gated PET images corresponding to a motion phase of the plurality ofmotion phases; identifying, in the anatomical image, one or moresub-regions associated with the physiological motion of the subject;determining, based on the one or more sub-regions in the anatomicalimage and the plurality of gated PET images, a reference motion phasethat matches a motion phase of the anatomical image among the pluralityof motion phases; and reconstructing, based on the reference motionphase and the gated PET data, an attenuation corrected PET imagecorresponding to a target motion phase.